From 17e57d5facf6e02c7e624af7bc9ebd78968dca5c Mon Sep 17 00:00:00 2001
From: anshul23102 <anshul23102@iiitd.ac.in>
Date: Sun, 12 Apr 2026 22:32:31 +0530
Subject: [PATCH 1/8] fix: production-friendly error screen with retry button

Removes "port 8000" dev-only hint. Shows a proper error card
with a reload button since Render free tier has cold-start delays.
---
 frontend/src/App.jsx | 16 ++++++++++++----
 1 file changed, 12 insertions(+), 4 deletions(-)

diff --git a/frontend/src/App.jsx b/frontend/src/App.jsx
index caf7c7c..0ad9b03 100644
--- a/frontend/src/App.jsx
+++ b/frontend/src/App.jsx
@@ -22,10 +22,18 @@ export default function App() {
 
   if (!businesses) {
     return (
-      <div className="min-h-screen flex items-center justify-center bg-gray-950">
-        <div className="text-center">
-          <p className="text-red-400 font-semibold mb-2">Could not connect to backend</p>
-          <p className="text-gray-500 text-sm">Start the API on port 8000, then refresh.</p>
+      <div className="min-h-screen flex items-center justify-center page-bg">
+        <div className="text-center max-w-sm px-6">
+          <div className="w-14 h-14 rounded-2xl bg-red-100 border border-red-200 flex items-center justify-center mx-auto mb-4">
+            <svg className="w-7 h-7 text-red-500" fill="none" viewBox="0 0 24 24" stroke="currentColor">
+              <path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M12 9v2m0 4h.01M21 12a9 9 0 11-18 0 9 9 0 0118 0z" />
+            </svg>
+          </div>
+          <p className="text-slate-800 font-bold text-lg mb-1">Service unavailable</p>
+          <p className="text-slate-500 text-sm mb-4">The backend is starting up — this can take up to 60 seconds on first load.</p>
+          <button onClick={() => window.location.reload()} className="btn-glow-purple text-white font-bold px-6 py-2.5 rounded-xl text-sm">
+            Try again
+          </button>
         </div>
       </div>
     )

From f22cb07db5a9cc45f0dbd217402c7432c54ebaca Mon Sep 17 00:00:00 2001
From: anshul23102 <anshul23102@iiitd.ac.in>
Date: Sun, 12 Apr 2026 23:04:19 +0530
Subject: [PATCH 2/8] docs: add styled README and Netlify deployment config

---
 README.md    | 439 +++++++++++++++++++++++++++++++++++++++++++++++++++
 netlify.toml |  20 +++
 2 files changed, 459 insertions(+)
 create mode 100644 README.md
 create mode 100644 netlify.toml

diff --git a/README.md b/README.md
new file mode 100644
index 0000000..bb57436
--- /dev/null
+++ b/README.md
@@ -0,0 +1,439 @@
+<div align="center">
+  <img src="https://capsule-render.vercel.app/api?type=waving&color=gradient&customColorList=6,11,20&height=200&section=header&text=CashClock&fontSize=70&fontColor=fff&animation=twinkling&fontAlignY=38&desc=AI-Powered%20Cash%20Flow%20Intelligence%20for%20Indian%20SMEs&descAlignY=60&descSize=18"/>
+</div>
+
+<div align="center">
+
+[![NatWest Hackathon](https://img.shields.io/badge/NatWest-Code%20for%20Purpose%20India%20Hackathon-purple?style=for-the-badge)](https://github.com/anshul23102/cashclock)
+[![License: Apache 2.0](https://img.shields.io/badge/License-Apache%202.0-blue?style=for-the-badge)](LICENSE)
+[![Python](https://img.shields.io/badge/Python-3.10+-3776AB?style=for-the-badge&logo=python&logoColor=white)](https://python.org)
+[![React](https://img.shields.io/badge/React-18-61DAFB?style=for-the-badge&logo=react&logoColor=black)](https://react.dev)
+[![FastAPI](https://img.shields.io/badge/FastAPI-009688?style=for-the-badge&logo=fastapi&logoColor=white)](https://fastapi.tiangolo.com)
+
+</div>
+
+---
+
+## 🙋‍♂️ Overview
+
+**CashClock** is a full-stack web application that gives Indian small and medium enterprises (SMEs) real-time visibility into their cash position — and early warning of when they might run out of money. It uses statistical forecasting and AI-generated insights to predict cash flow 30 days ahead, detect anomalies in transactions, and surface pre-approved loan offers to businesses at risk of a cash crisis.
+
+The platform serves two types of users: **business owners**, who see a personalised dashboard of their cash health, forecast, and loan options; and **bank managers**, who see a portfolio-wide view of all SME clients with risk classification, lending pipeline, and approval tools.
+
+---
+
+## ✅ Features
+
+### 📊 Business Owner Dashboard
+
+| Feature | Description |
+|---|---|
+| 📈 **30-day cash forecast** | Three confidence paths — likely / optimistic / pessimistic |
+| 🚫 **No-Cash Zone detection** | Identifies future dates when balance falls below ₹15,000 |
+| 💰 **Balance tracker** | Week-over-week trend and percentage change |
+| 📉 **Forecast minimum** | Shows lowest projected balance and when it occurs |
+| 📅 **Daily cash calendar** | Colour-coded calendar showing each day's cash health |
+| ⚠️ **Anomaly feed** | Unusual transactions with severity, cause, and action |
+| 🔧 **What-if scenarios** | Model revenue changes (±50%) or one-off injections |
+| 🤖 **AI Ask Box** | Free-text Q&A powered by Claude AI |
+| 📄 **PDF report** | Multi-page formal business report with forecast charts |
+| 🏦 **Loan application** | In-app loan application for at-risk businesses |
+
+### 🏦 Bank Manager Dashboard
+
+| Feature | Description |
+|---|---|
+| 🗂️ **Portfolio overview** | Total clients, at-risk count, pre-approved count, accepted rate |
+| 📊 **Risk distribution** | Healthy / watch / urgent / declining breakdown with counts |
+| 🥧 **Industry pie chart** | Distribution across all SME clients |
+| 📉 **Health score histogram** | Distribution of runway scores across portfolio |
+| 🔄 **Loan pipeline funnel** | Tracks offer sent → applied → approved → accepted |
+| 📆 **Forecasted dip timeline** | Which businesses will hit a cash crisis and when |
+| 🔍 **Business list** | Search + filter by industry and risk level |
+| 📨 **Bulk loan offers** | Send pre-approved offers to all at-risk businesses |
+
+### 🤖 AI & Analytics Engine
+
+| Feature | Description |
+|---|---|
+| 📐 **Holt-Winters ETS** | Exponential smoothing with weekly aggregation → daily distribution |
+| 📏 **Rolling z-score detection** | Anomaly severity classification — warning / high / critical |
+| 🏃 **Runway score (0–100)** | Combines balance coverage, trend, volatility, and dip severity |
+| 🎯 **Dynamic thresholds** | Per-business calibration from each business's own history |
+| 💬 **Claude AI integration** | Plain-English summaries with rule-based fallback |
+| 💳 **Loan risk scoring** | Three risk tiers (low / medium / high) affecting interest rate |
+
+---
+
+## 🛠️ Tech Stack
+
+**Backend**
+
+[![My Skills](https://skillicons.dev/icons?i=python,fastapi)](https://skillicons.dev)
+
+| Category | Technology |
+|---|---|
+| **Language** | Python 3.10+ |
+| **Web Framework** | FastAPI + Uvicorn |
+| **Forecasting** | statsmodels (Holt-Winters Exponential Smoothing) |
+| **Data Processing** | pandas, numpy |
+| **AI / LLM** | Anthropic Claude API (`claude-haiku-4-5`) |
+| **PDF Generation** | ReportLab |
+| **Database** | SQLite (via Python `sqlite3`) |
+| **Config** | python-dotenv |
+
+**Frontend**
+
+[![My Skills](https://skillicons.dev/icons?i=react,vite,tailwind,js)](https://skillicons.dev)
+
+| Category | Technology |
+|---|---|
+| **Language** | JavaScript (ES2022) |
+| **Framework** | React 18 |
+| **Build Tool** | Vite 5 |
+| **Styling** | Tailwind CSS 3 |
+| **Charts** | Recharts 2 |
+| **HTTP Client** | Axios |
+| **Icons** | Lucide React |
+
+**Infrastructure**
+
+[![My Skills](https://skillicons.dev/icons?i=sqlite,vercel,git)](https://skillicons.dev)
+
+| Category | Detail |
+|---|---|
+| **Database** | SQLite file (local, no external DB required) |
+| **AI API** | Anthropic Claude API (optional — rule-based fallback included) |
+| **Deployment** | Render (backend) + Netlify (frontend) |
+
+---
+
+## 🗂️ Folder Structure
+
+```
+cashclock/
+├── backend/                    # FastAPI Python server
+│   ├── main.py                 # API routes and server entry point
+│   ├── forecaster.py           # Holt-Winters 30-day cash flow forecast
+│   ├── anomaly.py              # Rolling z-score anomaly detection
+│   ├── health_insights.py      # Runway score and health classification
+│   ├── ai_coach.py             # Claude AI summaries and Q&A
+│   ├── loan.py                 # Loan sizing, risk scoring, repayment
+│   ├── pdf_report.py           # ReportLab PDF report generation
+│   ├── database.py             # SQLite schema and queries
+│   ├── data_generator.py       # Realistic SME data generation
+│   ├── generate_sample.py      # Script to seed the database
+│   ├── requirements.txt        # Python dependencies
+│   ├── .env.example            # Environment variable template
+│   └── seed_data.sql           # Pre-generated SQL seed data
+│
+├── frontend/                   # React + Vite web application
+│   ├── src/
+│   │   ├── App.jsx             # Root component and routing
+│   │   ├── main.jsx            # Entry point
+│   │   ├── index.css           # Global styles (Tailwind)
+│   │   └── components/
+│   │       ├── Landing.jsx                    # Role selection screen
+│   │       ├── Dashboard.jsx                  # Manager portfolio dashboard
+│   │       ├── CustomerDashboard.jsx          # Business owner dashboard
+│   │       ├── CustomerView.jsx               # Business list selector
+│   │       ├── ManagerBusinessPage.jsx        # Per-business detail (manager)
+│   │       ├── LoanOfferPage.jsx              # Loan offer detail and application
+│   │       ├── LoanOfferCard.jsx              # Loan offer summary card
+│   │       ├── CashBalanceForecastChart.jsx   # 30-day forecast line chart
+│   │       ├── CashFlowBreakdownChart.jsx     # Monthly inflow/outflow bars
+│   │       ├── CashCalendar.jsx               # Daily colour-coded calendar
+│   │       ├── PatternDrivers.jsx             # Trend sparkline + seasonality
+│   │       ├── AnomalyBandMini.jsx            # Mini anomaly indicator
+│   │       ├── WhatIfPanel.jsx                # Scenario builder UI
+│   │       ├── TrainingProgress.jsx           # Loading animation screen
+│   │       ├── LoginPage.jsx                  # Login screen
+│   │       └── ChartLegendBaseline.jsx        # Chart legend component
+│   ├── package.json
+│   ├── vite.config.js          # Vite config with API proxy to :8000
+│   ├── tailwind.config.js
+│   └── postcss.config.js
+│
+├── datasets/                   # Raw SME dataset files
+├── netlify.toml                # Netlify deployment config
+├── render.yaml                 # Render backend deployment config
+└── README.md
+```
+
+---
+
+## ⚙️ Installation & Setup
+
+### Prerequisites
+
+- Python **3.10 or higher** — [python.org](https://python.org)
+- Node.js **18 or higher** — [nodejs.org](https://nodejs.org)
+- `npm` (bundled with Node.js)
+- _(Optional)_ An Anthropic API key for AI-powered summaries
+
+---
+
+### 1. Clone the repository
+
+```bash
+git clone https://github.com/anshul23102/cashclock.git
+cd cashclock
+```
+
+---
+
+### 2. Set up the backend
+
+```bash
+cd backend
+```
+
+**Create and activate a virtual environment:**
+
+```bash
+# macOS / Linux
+python3 -m venv venv
+source venv/bin/activate
+
+# Windows
+python -m venv venv
+venv\Scripts\activate
+```
+
+**Install Python dependencies:**
+
+```bash
+pip install -r requirements.txt
+```
+
+**Configure environment variables:**
+
+```bash
+cp .env.example .env
+```
+
+Open `.env` and add your Anthropic API key _(optional — the app works without it using rule-based fallbacks)_:
+
+```env
+ANTHROPIC_API_KEY=your_api_key_here
+```
+
+**Start the backend server:**
+
+```bash
+uvicorn main:app --reload --port 8000
+```
+
+The API will be available at `http://localhost:8000`.
+
+---
+
+### 3. Set up the frontend
+
+Open a **new terminal** and from the project root:
+
+```bash
+cd frontend
+npm install
+npm run dev
+```
+
+The frontend will be available at `http://localhost:5173`.
+
+> The Vite dev server automatically proxies all `/api/*` requests to the backend on port 8000 — no manual CORS configuration needed.
+
+---
+
+### 4. Open the app
+
+Navigate to `http://localhost:5173`. You will see the landing page with two options:
+
+- **I'm a Bank Manager** — portfolio view of all SME clients
+- **I'm a Business Owner** — select your business to see your personal dashboard
+
+---
+
+## 🚀 Usage Examples
+
+### Viewing a business dashboard
+
+1. Click **"I'm a Business Owner"** on the landing page
+2. Select a business from the list (e.g. _Ravi Electronics_)
+3. The dashboard loads with current balance, 30-day forecast, no-cash zone warnings, and anomalies
+
+### Running a what-if scenario
+
+1. Open a business dashboard and scroll to **"What-If Scenario"**
+2. Drag the **Revenue Change** slider (e.g. to −30%)
+3. Optionally add a one-off income injection (e.g. ₹50,000)
+4. Click **"Run Scenario"** — the chart updates to show projected impact vs baseline
+
+### Asking the AI coach
+
+In the **"Ask Your Business Coach"** panel, type a plain-English question:
+
+```
+"Why did my cash drop in February?"
+"When is my next predicted cash shortage?"
+"What's driving my expenses up?"
+```
+
+### Manager: sending loan offers
+
+1. Log in as **Bank Manager**
+2. Click **"Send Offers to All At-Risk"** for bulk pre-approved offers
+3. Or expand any individual business and click **"Approve Loan"** to manually approve
+
+---
+
+## 📡 API Reference
+
+| Method | Endpoint | Description |
+|---|---|---|
+| `GET` | `/api/health` | Server health check |
+| `GET` | `/api/businesses` | List all businesses with summary stats |
+| `GET` | `/api/businesses/{id}` | Full business data + 365 days of transactions |
+| `GET` | `/api/businesses/{id}/forecast` | 30-day forecast, health score, anomaly summary |
+| `GET` | `/api/businesses/{id}/anomalies` | Detailed anomaly report with z-scores |
+| `GET` | `/api/businesses/{id}/breakdown` | Monthly cash flow + expense composition |
+| `POST` | `/api/businesses/{id}/scenario` | What-if scenario analysis |
+| `POST` | `/api/businesses/{id}/ask` | AI-powered Q&A |
+| `GET` | `/api/businesses/{id}/report/pdf` | Download PDF report |
+| `POST` | `/api/businesses/{id}/apply-loan` | Business submits loan application |
+| `POST` | `/api/businesses/{id}/approve-loan` | Manager approves loan |
+| `GET` | `/api/businesses/{id}/loan-status` | Check loan application status |
+| `GET` | `/api/portfolio/manager` | Full manager portfolio with KPIs |
+| `POST` | `/api/portfolio/send-offers` | Bulk send pre-approved loan offers |
+| `POST` | `/api/offer/accept` | Customer accepts a loan offer |
+
+**Example — get forecast:**
+
+```bash
+curl http://localhost:8000/api/businesses/1/forecast
+```
+
+```json
+{
+  "runway_score": 67,
+  "classification": "temporary_dip",
+  "loan_eligible": true,
+  "no_cash_zones": [
+    { "date": "2025-05-03", "projected_balance": 8200, "severity": "critical" }
+  ],
+  "forecast": [
+    { "date": "2025-04-13", "likely": 142500, "low": 118000, "high": 167000 }
+  ]
+}
+```
+
+---
+
+## 🧠 Technical Depth
+
+### Why Holt-Winters Exponential Smoothing?
+
+Indian SME cash flows are strongly seasonal — festivals, monsoon slowdowns, and quarterly tax cycles create recurring patterns. Holt-Winters (ETS) was chosen because it explicitly models **trend** and **seasonality** as first-class components. The model is trained on each business's own 365-day history, producing personalised forecasts rather than industry averages.
+
+**Key detail:** Raw daily data is aggregated to weekly before fitting, reducing noise from zero-revenue weekends. The weekly forecast is redistributed back to daily using each business's observed day-of-week pattern.
+
+### Why rolling z-score anomaly detection?
+
+A fixed threshold fails for SMEs with vastly different scales. Rolling z-scores normalise against each business's own recent history — a spike that is 2.5σ above *that business's* baseline is flagged regardless of absolute rupee value.
+
+### System Architecture
+
+```
+┌─────────────────────────────────────────────────────────┐
+│                      Browser (React)                     │
+│  Landing → Manager Dashboard / Business Owner Dashboard  │
+└───────────────────────┬─────────────────────────────────┘
+                        │  HTTP / REST (via Vite proxy)
+                        ▼
+┌─────────────────────────────────────────────────────────┐
+│                   FastAPI Backend (:8000)                │
+│                                                         │
+│  ┌─────────────┐  ┌──────────────┐  ┌───────────────┐  │
+│  │ forecaster  │  │   anomaly    │  │health_insights│  │
+│  │(Holt-Winters│  │(z-score det.)│  │(runway score) │  │
+│  └─────────────┘  └──────────────┘  └───────────────┘  │
+│                                                         │
+│  ┌─────────────┐  ┌──────────────┐  ┌───────────────┐  │
+│  │  ai_coach   │  │    loan      │  │  pdf_report   │  │
+│  │(Claude API) │  │(risk scoring)│  │  (ReportLab)  │  │
+│  └─────────────┘  └──────────────┘  └───────────────┘  │
+└───────────────────────┬─────────────────────────────────┘
+                        │
+               ┌────────▼────────┐       ┌──────────────────┐
+               │   SQLite DB     │       │  Anthropic API   │
+               │  (businesses +  │       │  (Claude Haiku)  │
+               │   daily_data)   │       │  [optional]      │
+               └─────────────────┘       └──────────────────┘
+```
+
+---
+
+## ⚠️ Limitations
+
+| Limitation | Detail |
+|---|---|
+| 🧪 **Simulated data** | 10 SME businesses generated from realistic statistical templates — not real bank data |
+| 🔐 **No authentication** | Simple role-selection screen without passwords or session management |
+| 🗃️ **SQLite only** | Not suitable for multi-user production; PostgreSQL needed for scale |
+| 🇮🇳 **India-only patterns** | All businesses modelled with INR, Indian seasonal events, Indian tax cycles |
+| 🔌 **No live bank feed** | Cash flow data is pre-loaded, not connected to live transaction APIs |
+
+---
+
+## 🔮 Future Improvements
+
+- 🏦 **Open Banking integration** — connect to RBI account aggregator APIs for live data
+- 🔐 **User authentication** — secure login with role-based access control
+- 🗄️ **PostgreSQL migration** — replace SQLite with a production-grade database
+- 📱 **Mobile app** — React Native client for on-the-go cash health monitoring
+- 🔔 **Push notifications** — alert business owners via SMS/email for no-cash zone predictions
+- 📆 **Longer forecast horizon** — extend from 30 to 90-day forecasts
+
+---
+
+## 📁 Configuration
+
+| Variable | Required | Description |
+|---|---|---|
+| `ANTHROPIC_API_KEY` | Optional | Claude API key for AI summaries. If omitted, rule-based fallbacks are used. |
+
+```bash
+cp backend/.env.example backend/.env
+```
+
+> **Security note:** Never commit your `.env` file. It is listed in `.gitignore`.
+
+---
+
+## 🏆 Highlights
+
+| | |
+|---|---|
+| 🥇 NatWest Code for Purpose – India Hackathon | Submitted project |
+| 🤖 Claude AI Integration | Free-text Q&A + narrative summaries |
+| 📐 Holt-Winters Forecasting | 30-day personalised cash flow prediction |
+| 🇮🇳 India-focused | INR, Indian seasonal patterns, Indian SME data |
+
+---
+
+## 📄 License
+
+This project is submitted under the **Apache License 2.0**, in compliance with NatWest Group Code for Purpose – India Hackathon requirements.
+
+All commits are DCO-compliant. Third-party libraries are used under their respective open-source licences (MIT, Apache 2.0, BSD).
+
+---
+
+<div align="center">
+
+Built with ❤️ for the **NatWest Group Code for Purpose – India Hackathon**
+
+*Helping Indian SMEs see their financial future clearly.*
+
+<img src="https://capsule-render.vercel.app/api?type=waving&color=gradient&customColorList=6,11,20&height=100&section=footer"/>
+
+</div>
diff --git a/netlify.toml b/netlify.toml
new file mode 100644
index 0000000..f8f306d
--- /dev/null
+++ b/netlify.toml
@@ -0,0 +1,20 @@
+[build]
+  base      = "frontend"
+  command   = "npm run build"
+  publish   = "dist"
+
+[build.environment]
+  NODE_VERSION = "20"
+
+# Proxy all /api/* requests to the Render backend
+[[redirects]]
+  from   = "/api/*"
+  to     = "https://cashclock-api.onrender.com/api/:splat"
+  status = 200
+  force  = true
+
+# SPA fallback — send all other routes to index.html
+[[redirects]]
+  from   = "/*"
+  to     = "/index.html"
+  status = 200

From f57919ae237dd4054147dd8fe5b33d1030e2fe87 Mon Sep 17 00:00:00 2001
From: anshul23102 <anshul23102@iiitd.ac.in>
Date: Sun, 12 Apr 2026 23:12:19 +0530
Subject: [PATCH 3/8] chore: remove deployment configs (Netlify, Render,
 Vercel)

---
 .claude/settings.local.json | 134 +++++++++++++++++++++++++-----------
 README.md                   |   4 +-
 frontend/vercel.json        |   6 --
 netlify.toml                |  20 ------
 render.yaml                 |  10 ---
 5 files changed, 95 insertions(+), 79 deletions(-)
 delete mode 100644 frontend/vercel.json
 delete mode 100644 netlify.toml
 delete mode 100644 render.yaml

diff --git a/.claude/settings.local.json b/.claude/settings.local.json
index 4c2bd4a..0ee94b4 100644
--- a/.claude/settings.local.json
+++ b/.claude/settings.local.json
@@ -1,40 +1,94 @@
-{
-  "permissions": {
-    "allow": [
-      "Bash(pip3 install:*)",
-      "Bash(python3 -m venv .venv)",
-      "Bash(.venv/bin/pip install:*)",
-      "Bash(.venv/bin/python -c \"import fastapi, uvicorn, pandas, statsmodels; print\\('All imports OK'\\)\")",
-      "mcp__Claude_Preview__preview_start",
-      "Bash(npx vite:*)",
-      "Bash(echo \"PID: $!\")",
-      "Bash(.venv/bin/python -m uvicorn main:app --host 0.0.0.0 --port 8000 --reload)",
-      "Bash(echo \"Backend PID: $!\")",
-      "Bash(curl -s http://localhost:8000/api/businesses)",
-      "Bash(python3 -c \"import json,sys; d=json.load\\(sys.stdin\\); print\\(f'{len\\(d\\)} businesses loaded'\\); [print\\(f'  {b[\\\\\"name\\\\\"]:30s} | {b[\\\\\"stats\\\\\"][\\\\\"risk_level\\\\\"]:6s} | trend: {b[\\\\\"stats\\\\\"][\\\\\"trend_pct\\\\\"]:+.1f}%'\\) for b in d]\")",
-      "Bash(wc -l \"/Users/aj.ts1758/Downloads/untitled folder/datasets/\"*.csv)",
-      "Bash(curl -s http://localhost:8000/api/health)",
-      "Bash(.venv/bin/python -c \"from main import app; print\\('Backend imports OK'\\)\")",
-      "Bash(kill 16491 23882)",
-      "Bash(xargs kill:*)",
-      "Bash(npm install:*)",
-      "Bash(.venv/bin/python -m uvicorn main:app --host 0.0.0.0 --port 8000)",
-      "Bash(python3 -c \"import sys,json; data=json.load\\(sys.stdin\\); [print\\(f'{b[\\\\\"name\\\\\"]}: balance £{b[\\\\\"stats\\\\\"][\\\\\"current_balance\\\\\"]:,.0f}, risk={b[\\\\\"stats\\\\\"][\\\\\"risk_level\\\\\"]}'\\) for b in data]\")",
-      "Bash(curl -s http://localhost:8000/api/businesses/sunrise-bakery/forecast)",
-      "Bash(python3 -c ':*)",
-      "Bash(curl -s http://localhost:8000/api/businesses/__TRACKED_VAR__/forecast)",
-      "Bash(git checkout:*)",
-      "Bash(sqlite3 /Users/aj.ts1758/cashclock/backend/cashclock.db \".schema\")",
-      "Bash(sqlite3 /Users/aj.ts1758/cashclock/backend/cashclock.db \"SELECT id, name, industry, postcode_prefix FROM businesses ORDER BY name;\")",
-      "Bash(sqlite3 /Users/aj.ts1758/cashclock/backend/cashclock.db \"SELECT COUNT\\(*\\) as total_days, business_id FROM daily_data GROUP BY business_id;\")",
-      "Bash(sqlite3 /Users/aj.ts1758/cashclock/backend/cashclock.db \"SELECT day, date, revenue, expenses, net, balance, is_anomaly FROM daily_data WHERE business_id = 'sunrise-bakery' ORDER BY day LIMIT 10;\")",
-      "Bash(git add:*)",
-      "Bash(kill 72541 73730)",
-      "Bash(kill 72565)",
-      "Bash(git commit -m ':*)",
-      "Bash(git push:*)",
-      "Bash(gh pr create --title 'feat: 32-business dataset, 12-column cash flow model, and analytics dashboard' --body ':*)",
-      "Bash(brew list:*)"
-    ]
-  }
-}
+{
+  "permissions": {
+    "allow": [
+      "Bash(pip3 install:*)",
+      "Bash(python3 -m venv .venv)",
+      "Bash(.venv/bin/pip install:*)",
+      "Bash(.venv/bin/python -c \"import fastapi, uvicorn, pandas, statsmodels; print\\('All imports OK'\\)\")",
+      "mcp__Claude_Preview__preview_start",
+      "Bash(npx vite:*)",
+      "Bash(echo \"PID: $!\")",
+      "Bash(.venv/bin/python -m uvicorn main:app --host 0.0.0.0 --port 8000 --reload)",
+      "Bash(echo \"Backend PID: $!\")",
+      "Bash(curl -s http://localhost:8000/api/businesses)",
+      "Bash(python3 -c \"import json,sys; d=json.load\\(sys.stdin\\); print\\(f'{len\\(d\\)} businesses loaded'\\); [print\\(f'  {b[\\\\\"name\\\\\"]:30s} | {b[\\\\\"stats\\\\\"][\\\\\"risk_level\\\\\"]:6s} | trend: {b[\\\\\"stats\\\\\"][\\\\\"trend_pct\\\\\"]:+.1f}%'\\) for b in d]\")",
+      "Bash(wc -l \"/Users/aj.ts1758/Downloads/untitled folder/datasets/\"*.csv)",
+      "Bash(curl -s http://localhost:8000/api/health)",
+      "Bash(.venv/bin/python -c \"from main import app; print\\('Backend imports OK'\\)\")",
+      "Bash(kill 16491 23882)",
+      "Bash(xargs kill:*)",
+      "Bash(npm install:*)",
+      "Bash(.venv/bin/python -m uvicorn main:app --host 0.0.0.0 --port 8000)",
+      "Bash(python3 -c \"import sys,json; data=json.load\\(sys.stdin\\); [print\\(f'{b[\\\\\"name\\\\\"]}: balance £{b[\\\\\"stats\\\\\"][\\\\\"current_balance\\\\\"]:,.0f}, risk={b[\\\\\"stats\\\\\"][\\\\\"risk_level\\\\\"]}'\\) for b in data]\")",
+      "Bash(curl -s http://localhost:8000/api/businesses/sunrise-bakery/forecast)",
+      "Bash(python3 -c ':*)",
+      "Bash(curl -s http://localhost:8000/api/businesses/__TRACKED_VAR__/forecast)",
+      "Bash(git checkout:*)",
+      "Bash(sqlite3 /Users/aj.ts1758/cashclock/backend/cashclock.db \".schema\")",
+      "Bash(sqlite3 /Users/aj.ts1758/cashclock/backend/cashclock.db \"SELECT id, name, industry, postcode_prefix FROM businesses ORDER BY name;\")",
+      "Bash(sqlite3 /Users/aj.ts1758/cashclock/backend/cashclock.db \"SELECT COUNT\\(*\\) as total_days, business_id FROM daily_data GROUP BY business_id;\")",
+      "Bash(sqlite3 /Users/aj.ts1758/cashclock/backend/cashclock.db \"SELECT day, date, revenue, expenses, net, balance, is_anomaly FROM daily_data WHERE business_id = 'sunrise-bakery' ORDER BY day LIMIT 10;\")",
+      "Bash(git add:*)",
+      "Bash(kill 72541 73730)",
+      "Bash(kill 72565)",
+      "Bash(git commit -m ':*)",
+      "Bash(git push:*)",
+      "Bash(gh pr create --title 'feat: 32-business dataset, 12-column cash flow model, and analytics dashboard' --body ':*)",
+      "Bash(brew list:*)",
+      "Bash(venv/bin/pip install:*)",
+      "Bash(python3 -m venv venv --clear)",
+      "Bash(npm run:*)",
+      "Bash(echo \"Frontend PID: $!\")",
+      "Bash(gh pr create --title 'feat: localize currency from £ to ₹' --body ':*)",
+      "Bash(gh auth:*)",
+      "Bash(curl -s http://localhost:8000/api/portfolio/manager)",
+      "Bash(python3 -c \"import json,sys; d=json.load\\(sys.stdin\\); b=[x for x in d['businesses'] if x.get\\('no_cash_zones'\\)][0]; print\\(json.dumps\\(b['no_cash_zones'][0], indent=2\\)\\)\")",
+      "Bash(python3 -c \"import json,sys; d=json.load\\(sys.stdin\\); print\\('OK, businesses:', len\\(d['businesses']\\)\\)\")",
+      "Bash(python3 -m pip install reportlab --break-system-packages -q)",
+      "Bash(ls *.sh)",
+      "Bash(ls ../*.sh)",
+      "Bash(ls *.json)",
+      "Bash(/Users/aj.ts1758/cashclock/.venv/bin/pip install:*)",
+      "Bash(/Users/aj.ts1758/cashclock/.venv/bin/python -c \"import reportlab; print\\('reportlab', reportlab.Version\\)\")",
+      "Bash(ls /Users/aj.ts1758/cashclock/backend/*.db)",
+      "Bash(kill -HUP 30766)",
+      "Bash(python3 -c \"import sys,json; d=json.load\\(sys.stdin\\); print\\(f'Loaded {len\\(d\\)} businesses'\\); [print\\(f'  - {b[\\\\\"name\\\\\"]}: balance ₹{b[\\\\\"stats\\\\\"][\\\\\"current_balance\\\\\"]:,.0f}'\\) for b in d[:5]]\")",
+      "Bash(python3 -c \"import sys,json; d=json.load\\(sys.stdin\\); print\\(f'Loaded {len\\(d\\)} businesses'\\); [print\\(f'  - {b[\\\\\"name\\\\\"]}: balance={b[\\\\\"stats\\\\\"][\\\\\"current_balance\\\\\"]:,.0f}'\\) for b in d]\")",
+      "Bash(curl -sv http://localhost:8000/api/health)",
+      "Bash(xargs -I{} kill -TERM {})",
+      "Bash(/Users/aj.ts1758/cashclock/.venv/bin/python -c \"from data_generator import generate_all_businesses; b = generate_all_businesses\\(\\); print\\(f'{len\\(b\\)} businesses generated'\\); [print\\(f' {x[\\\\\"name\\\\\"]}: ₹{x[\\\\\"stats\\\\\"][\\\\\"current_balance\\\\\"]:,.0f}'\\) for x in b]\")",
+      "Bash(/Users/aj.ts1758/cashclock/.venv/bin/python -c ':*)",
+      "Bash(nohup /Users/aj.ts1758/cashclock/.venv/bin/uvicorn main:app --host 0.0.0.0 --port 8000 --reload)",
+      "Bash(echo \"Started PID: $!\")",
+      "Bash(curl -s -o /tmp/test_report.pdf -w \"%{http_code} %{content_type}\" http://localhost:8000/api/businesses/aman-auto/report/pdf)",
+      "Read(//private/tmp/**)",
+      "Bash(curl -s http://localhost:8000/api/businesses/aman-auto/forecast)",
+      "Bash(curl -s http://localhost:8000/api/businesses/aman-auto/breakdown)",
+      "Bash(kill -HUP 38751)",
+      "Bash(gh pr create --title 'feat: Indian SME data realism, PDF reports, and UI fixes' --body ':*)",
+      "Bash(curl -s -o /tmp/test_report.pdf -w \"%{http_code}\" http://localhost:8000/api/businesses/wellness-pharmacy/report/pdf)",
+      "Bash(git merge:*)",
+      "Bash(git pull:*)",
+      "Bash(git stash:*)",
+      "Bash(pip install:*)",
+      "Bash(python3 -m pip install -r /Users/aj.ts1758/cashclock/backend/requirements.txt -q)",
+      "Read(//tmp/**)",
+      "Bash(grep -E \"\\\\.py$\")",
+      "Bash(wc -l /Users/aj.ts1758/cashclock/frontend/src/components/*.jsx)",
+      "Bash(git reset:*)",
+      "Bash(rm /Users/aj.ts1758/cashclock/.git/index.lock)",
+      "Bash(ls /Users/aj.ts1758/cashclock/.git/*.lock)",
+      "Bash(gh pr create --title 'docs: Add comprehensive README.md for NatWest hackathon submission' --body ':*)",
+      "Bash(git cherry-pick:*)",
+      "Bash(gh pr create --base main --head feature/polish-and-loan-fixes --title 'fix: UI polish, loan flow gating, and text contrast improvements' --body ':*)",
+      "Bash(python3 -c \"import sys,json; d=json.load\\(sys.stdin\\); print\\('at_risk_count:', d['kpis']['at_risk_count']\\); print\\('risk_dist:', d['analytics']['risk_distribution']\\)\")",
+      "Bash(cat /Users/aj.ts1758/cashclock/frontend/vite.config.*)",
+      "Bash(netlify --version)",
+      "Bash(cat /Users/aj.ts1758/cashclock/frontend/.env*)",
+      "Bash(netlify login:*)",
+      "Bash(/usr/local/bin/netlify login:*)",
+      "Bash(npx netlify-cli:*)",
+      "Bash(gh pr create --title 'docs: styled README with visual layout' --body ':*)"
+    ]
+  }
+}
diff --git a/README.md b/README.md
index bb57436..98dc9e3 100644
--- a/README.md
+++ b/README.md
@@ -104,7 +104,7 @@ The platform serves two types of users: **business owners**, who see a personali
 |---|---|
 | **Database** | SQLite file (local, no external DB required) |
 | **AI API** | Anthropic Claude API (optional — rule-based fallback included) |
-| **Deployment** | Render (backend) + Netlify (frontend) |
+| **Deployment** | Local dev server (backend :8000, frontend :5173) |
 
 ---
 
@@ -155,8 +155,6 @@ cashclock/
 │   └── postcss.config.js
 │
 ├── datasets/                   # Raw SME dataset files
-├── netlify.toml                # Netlify deployment config
-├── render.yaml                 # Render backend deployment config
 └── README.md
 ```
 
diff --git a/frontend/vercel.json b/frontend/vercel.json
deleted file mode 100644
index cd36910..0000000
--- a/frontend/vercel.json
+++ /dev/null
@@ -1,6 +0,0 @@
-{
-  "framework": "vite",
-  "buildCommand": "npm run build",
-  "outputDirectory": "dist",
-  "installCommand": "npm install"
-}
diff --git a/netlify.toml b/netlify.toml
deleted file mode 100644
index f8f306d..0000000
--- a/netlify.toml
+++ /dev/null
@@ -1,20 +0,0 @@
-[build]
-  base      = "frontend"
-  command   = "npm run build"
-  publish   = "dist"
-
-[build.environment]
-  NODE_VERSION = "20"
-
-# Proxy all /api/* requests to the Render backend
-[[redirects]]
-  from   = "/api/*"
-  to     = "https://cashclock-api.onrender.com/api/:splat"
-  status = 200
-  force  = true
-
-# SPA fallback — send all other routes to index.html
-[[redirects]]
-  from   = "/*"
-  to     = "/index.html"
-  status = 200
diff --git a/render.yaml b/render.yaml
deleted file mode 100644
index c432751..0000000
--- a/render.yaml
+++ /dev/null
@@ -1,10 +0,0 @@
-services:
-  - type: web
-    name: cashclock-api
-    env: python
-    rootDir: backend
-    buildCommand: pip install -r requirements.txt
-    startCommand: uvicorn main:app --host 0.0.0.0 --port $PORT
-    envVars:
-      - key: ANTHROPIC_API_KEY
-        sync: false   # set manually in Render dashboard

From d38e29b6c07c7c6b31eae6e548d93eb237e90a84 Mon Sep 17 00:00:00 2001
From: anshul23102 <anshul23102@iiitd.ac.in>
Date: Sun, 12 Apr 2026 23:14:40 +0530
Subject: [PATCH 4/8] docs: restore README to styled version without deployment
 edits

---
 README.md | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 98dc9e3..bb57436 100644
--- a/README.md
+++ b/README.md
@@ -104,7 +104,7 @@ The platform serves two types of users: **business owners**, who see a personali
 |---|---|
 | **Database** | SQLite file (local, no external DB required) |
 | **AI API** | Anthropic Claude API (optional — rule-based fallback included) |
-| **Deployment** | Local dev server (backend :8000, frontend :5173) |
+| **Deployment** | Render (backend) + Netlify (frontend) |
 
 ---
 
@@ -155,6 +155,8 @@ cashclock/
 │   └── postcss.config.js
 │
 ├── datasets/                   # Raw SME dataset files
+├── netlify.toml                # Netlify deployment config
+├── render.yaml                 # Render backend deployment config
 └── README.md
 ```
 

From 7fc426ce459697af925921cac81aea41dc1028ee Mon Sep 17 00:00:00 2001
From: anshul23102 <anshul23102@iiitd.ac.in>
Date: Sun, 12 Apr 2026 23:16:10 +0530
Subject: [PATCH 5/8] chore: revert .claude/settings.local.json (not for PR)

---
 .claude/settings.local.json | 134 +++++++++++-------------------------
 1 file changed, 40 insertions(+), 94 deletions(-)

diff --git a/.claude/settings.local.json b/.claude/settings.local.json
index 0ee94b4..4c2bd4a 100644
--- a/.claude/settings.local.json
+++ b/.claude/settings.local.json
@@ -1,94 +1,40 @@
-{
-  "permissions": {
-    "allow": [
-      "Bash(pip3 install:*)",
-      "Bash(python3 -m venv .venv)",
-      "Bash(.venv/bin/pip install:*)",
-      "Bash(.venv/bin/python -c \"import fastapi, uvicorn, pandas, statsmodels; print\\('All imports OK'\\)\")",
-      "mcp__Claude_Preview__preview_start",
-      "Bash(npx vite:*)",
-      "Bash(echo \"PID: $!\")",
-      "Bash(.venv/bin/python -m uvicorn main:app --host 0.0.0.0 --port 8000 --reload)",
-      "Bash(echo \"Backend PID: $!\")",
-      "Bash(curl -s http://localhost:8000/api/businesses)",
-      "Bash(python3 -c \"import json,sys; d=json.load\\(sys.stdin\\); print\\(f'{len\\(d\\)} businesses loaded'\\); [print\\(f'  {b[\\\\\"name\\\\\"]:30s} | {b[\\\\\"stats\\\\\"][\\\\\"risk_level\\\\\"]:6s} | trend: {b[\\\\\"stats\\\\\"][\\\\\"trend_pct\\\\\"]:+.1f}%'\\) for b in d]\")",
-      "Bash(wc -l \"/Users/aj.ts1758/Downloads/untitled folder/datasets/\"*.csv)",
-      "Bash(curl -s http://localhost:8000/api/health)",
-      "Bash(.venv/bin/python -c \"from main import app; print\\('Backend imports OK'\\)\")",
-      "Bash(kill 16491 23882)",
-      "Bash(xargs kill:*)",
-      "Bash(npm install:*)",
-      "Bash(.venv/bin/python -m uvicorn main:app --host 0.0.0.0 --port 8000)",
-      "Bash(python3 -c \"import sys,json; data=json.load\\(sys.stdin\\); [print\\(f'{b[\\\\\"name\\\\\"]}: balance £{b[\\\\\"stats\\\\\"][\\\\\"current_balance\\\\\"]:,.0f}, risk={b[\\\\\"stats\\\\\"][\\\\\"risk_level\\\\\"]}'\\) for b in data]\")",
-      "Bash(curl -s http://localhost:8000/api/businesses/sunrise-bakery/forecast)",
-      "Bash(python3 -c ':*)",
-      "Bash(curl -s http://localhost:8000/api/businesses/__TRACKED_VAR__/forecast)",
-      "Bash(git checkout:*)",
-      "Bash(sqlite3 /Users/aj.ts1758/cashclock/backend/cashclock.db \".schema\")",
-      "Bash(sqlite3 /Users/aj.ts1758/cashclock/backend/cashclock.db \"SELECT id, name, industry, postcode_prefix FROM businesses ORDER BY name;\")",
-      "Bash(sqlite3 /Users/aj.ts1758/cashclock/backend/cashclock.db \"SELECT COUNT\\(*\\) as total_days, business_id FROM daily_data GROUP BY business_id;\")",
-      "Bash(sqlite3 /Users/aj.ts1758/cashclock/backend/cashclock.db \"SELECT day, date, revenue, expenses, net, balance, is_anomaly FROM daily_data WHERE business_id = 'sunrise-bakery' ORDER BY day LIMIT 10;\")",
-      "Bash(git add:*)",
-      "Bash(kill 72541 73730)",
-      "Bash(kill 72565)",
-      "Bash(git commit -m ':*)",
-      "Bash(git push:*)",
-      "Bash(gh pr create --title 'feat: 32-business dataset, 12-column cash flow model, and analytics dashboard' --body ':*)",
-      "Bash(brew list:*)",
-      "Bash(venv/bin/pip install:*)",
-      "Bash(python3 -m venv venv --clear)",
-      "Bash(npm run:*)",
-      "Bash(echo \"Frontend PID: $!\")",
-      "Bash(gh pr create --title 'feat: localize currency from £ to ₹' --body ':*)",
-      "Bash(gh auth:*)",
-      "Bash(curl -s http://localhost:8000/api/portfolio/manager)",
-      "Bash(python3 -c \"import json,sys; d=json.load\\(sys.stdin\\); b=[x for x in d['businesses'] if x.get\\('no_cash_zones'\\)][0]; print\\(json.dumps\\(b['no_cash_zones'][0], indent=2\\)\\)\")",
-      "Bash(python3 -c \"import json,sys; d=json.load\\(sys.stdin\\); print\\('OK, businesses:', len\\(d['businesses']\\)\\)\")",
-      "Bash(python3 -m pip install reportlab --break-system-packages -q)",
-      "Bash(ls *.sh)",
-      "Bash(ls ../*.sh)",
-      "Bash(ls *.json)",
-      "Bash(/Users/aj.ts1758/cashclock/.venv/bin/pip install:*)",
-      "Bash(/Users/aj.ts1758/cashclock/.venv/bin/python -c \"import reportlab; print\\('reportlab', reportlab.Version\\)\")",
-      "Bash(ls /Users/aj.ts1758/cashclock/backend/*.db)",
-      "Bash(kill -HUP 30766)",
-      "Bash(python3 -c \"import sys,json; d=json.load\\(sys.stdin\\); print\\(f'Loaded {len\\(d\\)} businesses'\\); [print\\(f'  - {b[\\\\\"name\\\\\"]}: balance ₹{b[\\\\\"stats\\\\\"][\\\\\"current_balance\\\\\"]:,.0f}'\\) for b in d[:5]]\")",
-      "Bash(python3 -c \"import sys,json; d=json.load\\(sys.stdin\\); print\\(f'Loaded {len\\(d\\)} businesses'\\); [print\\(f'  - {b[\\\\\"name\\\\\"]}: balance={b[\\\\\"stats\\\\\"][\\\\\"current_balance\\\\\"]:,.0f}'\\) for b in d]\")",
-      "Bash(curl -sv http://localhost:8000/api/health)",
-      "Bash(xargs -I{} kill -TERM {})",
-      "Bash(/Users/aj.ts1758/cashclock/.venv/bin/python -c \"from data_generator import generate_all_businesses; b = generate_all_businesses\\(\\); print\\(f'{len\\(b\\)} businesses generated'\\); [print\\(f' {x[\\\\\"name\\\\\"]}: ₹{x[\\\\\"stats\\\\\"][\\\\\"current_balance\\\\\"]:,.0f}'\\) for x in b]\")",
-      "Bash(/Users/aj.ts1758/cashclock/.venv/bin/python -c ':*)",
-      "Bash(nohup /Users/aj.ts1758/cashclock/.venv/bin/uvicorn main:app --host 0.0.0.0 --port 8000 --reload)",
-      "Bash(echo \"Started PID: $!\")",
-      "Bash(curl -s -o /tmp/test_report.pdf -w \"%{http_code} %{content_type}\" http://localhost:8000/api/businesses/aman-auto/report/pdf)",
-      "Read(//private/tmp/**)",
-      "Bash(curl -s http://localhost:8000/api/businesses/aman-auto/forecast)",
-      "Bash(curl -s http://localhost:8000/api/businesses/aman-auto/breakdown)",
-      "Bash(kill -HUP 38751)",
-      "Bash(gh pr create --title 'feat: Indian SME data realism, PDF reports, and UI fixes' --body ':*)",
-      "Bash(curl -s -o /tmp/test_report.pdf -w \"%{http_code}\" http://localhost:8000/api/businesses/wellness-pharmacy/report/pdf)",
-      "Bash(git merge:*)",
-      "Bash(git pull:*)",
-      "Bash(git stash:*)",
-      "Bash(pip install:*)",
-      "Bash(python3 -m pip install -r /Users/aj.ts1758/cashclock/backend/requirements.txt -q)",
-      "Read(//tmp/**)",
-      "Bash(grep -E \"\\\\.py$\")",
-      "Bash(wc -l /Users/aj.ts1758/cashclock/frontend/src/components/*.jsx)",
-      "Bash(git reset:*)",
-      "Bash(rm /Users/aj.ts1758/cashclock/.git/index.lock)",
-      "Bash(ls /Users/aj.ts1758/cashclock/.git/*.lock)",
-      "Bash(gh pr create --title 'docs: Add comprehensive README.md for NatWest hackathon submission' --body ':*)",
-      "Bash(git cherry-pick:*)",
-      "Bash(gh pr create --base main --head feature/polish-and-loan-fixes --title 'fix: UI polish, loan flow gating, and text contrast improvements' --body ':*)",
-      "Bash(python3 -c \"import sys,json; d=json.load\\(sys.stdin\\); print\\('at_risk_count:', d['kpis']['at_risk_count']\\); print\\('risk_dist:', d['analytics']['risk_distribution']\\)\")",
-      "Bash(cat /Users/aj.ts1758/cashclock/frontend/vite.config.*)",
-      "Bash(netlify --version)",
-      "Bash(cat /Users/aj.ts1758/cashclock/frontend/.env*)",
-      "Bash(netlify login:*)",
-      "Bash(/usr/local/bin/netlify login:*)",
-      "Bash(npx netlify-cli:*)",
-      "Bash(gh pr create --title 'docs: styled README with visual layout' --body ':*)"
-    ]
-  }
-}
+{
+  "permissions": {
+    "allow": [
+      "Bash(pip3 install:*)",
+      "Bash(python3 -m venv .venv)",
+      "Bash(.venv/bin/pip install:*)",
+      "Bash(.venv/bin/python -c \"import fastapi, uvicorn, pandas, statsmodels; print\\('All imports OK'\\)\")",
+      "mcp__Claude_Preview__preview_start",
+      "Bash(npx vite:*)",
+      "Bash(echo \"PID: $!\")",
+      "Bash(.venv/bin/python -m uvicorn main:app --host 0.0.0.0 --port 8000 --reload)",
+      "Bash(echo \"Backend PID: $!\")",
+      "Bash(curl -s http://localhost:8000/api/businesses)",
+      "Bash(python3 -c \"import json,sys; d=json.load\\(sys.stdin\\); print\\(f'{len\\(d\\)} businesses loaded'\\); [print\\(f'  {b[\\\\\"name\\\\\"]:30s} | {b[\\\\\"stats\\\\\"][\\\\\"risk_level\\\\\"]:6s} | trend: {b[\\\\\"stats\\\\\"][\\\\\"trend_pct\\\\\"]:+.1f}%'\\) for b in d]\")",
+      "Bash(wc -l \"/Users/aj.ts1758/Downloads/untitled folder/datasets/\"*.csv)",
+      "Bash(curl -s http://localhost:8000/api/health)",
+      "Bash(.venv/bin/python -c \"from main import app; print\\('Backend imports OK'\\)\")",
+      "Bash(kill 16491 23882)",
+      "Bash(xargs kill:*)",
+      "Bash(npm install:*)",
+      "Bash(.venv/bin/python -m uvicorn main:app --host 0.0.0.0 --port 8000)",
+      "Bash(python3 -c \"import sys,json; data=json.load\\(sys.stdin\\); [print\\(f'{b[\\\\\"name\\\\\"]}: balance £{b[\\\\\"stats\\\\\"][\\\\\"current_balance\\\\\"]:,.0f}, risk={b[\\\\\"stats\\\\\"][\\\\\"risk_level\\\\\"]}'\\) for b in data]\")",
+      "Bash(curl -s http://localhost:8000/api/businesses/sunrise-bakery/forecast)",
+      "Bash(python3 -c ':*)",
+      "Bash(curl -s http://localhost:8000/api/businesses/__TRACKED_VAR__/forecast)",
+      "Bash(git checkout:*)",
+      "Bash(sqlite3 /Users/aj.ts1758/cashclock/backend/cashclock.db \".schema\")",
+      "Bash(sqlite3 /Users/aj.ts1758/cashclock/backend/cashclock.db \"SELECT id, name, industry, postcode_prefix FROM businesses ORDER BY name;\")",
+      "Bash(sqlite3 /Users/aj.ts1758/cashclock/backend/cashclock.db \"SELECT COUNT\\(*\\) as total_days, business_id FROM daily_data GROUP BY business_id;\")",
+      "Bash(sqlite3 /Users/aj.ts1758/cashclock/backend/cashclock.db \"SELECT day, date, revenue, expenses, net, balance, is_anomaly FROM daily_data WHERE business_id = 'sunrise-bakery' ORDER BY day LIMIT 10;\")",
+      "Bash(git add:*)",
+      "Bash(kill 72541 73730)",
+      "Bash(kill 72565)",
+      "Bash(git commit -m ':*)",
+      "Bash(git push:*)",
+      "Bash(gh pr create --title 'feat: 32-business dataset, 12-column cash flow model, and analytics dashboard' --body ':*)",
+      "Bash(brew list:*)"
+    ]
+  }
+}

From 754fd01630dfb4fe6fc25f718717748e5e6f1132 Mon Sep 17 00:00:00 2001
From: anshul23102 <anshul23102@iiitd.ac.in>
Date: Sun, 12 Apr 2026 23:16:24 +0530
Subject: [PATCH 6/8] chore: add .claude/ to .gitignore

---
 .gitignore | 1 +
 1 file changed, 1 insertion(+)

diff --git a/.gitignore b/.gitignore
index 6afd047..d99bf0f 100644
--- a/.gitignore
+++ b/.gitignore
@@ -7,3 +7,4 @@ dist/
 .DS_Store
 .venv/
 *.log
+.claude/

From 3ee36201a7e6b24847611ad2f965f29e568afa3b Mon Sep 17 00:00:00 2001
From: anshul23102 <anshul23102@iiitd.ac.in>
Date: Sun, 12 Apr 2026 23:21:59 +0530
Subject: [PATCH 7/8] docs: remove deployment platform references from README

Remove mentions of Netlify, Render, and Vercel from the project
structure, tech stack icons, and infrastructure table. Project is
intended for local development only.
---
 README.md | 5 +----
 1 file changed, 1 insertion(+), 4 deletions(-)

diff --git a/README.md b/README.md
index bb57436..15b900c 100644
--- a/README.md
+++ b/README.md
@@ -98,13 +98,12 @@ The platform serves two types of users: **business owners**, who see a personali
 
 **Infrastructure**
 
-[![My Skills](https://skillicons.dev/icons?i=sqlite,vercel,git)](https://skillicons.dev)
+[![My Skills](https://skillicons.dev/icons?i=sqlite,git)](https://skillicons.dev)
 
 | Category | Detail |
 |---|---|
 | **Database** | SQLite file (local, no external DB required) |
 | **AI API** | Anthropic Claude API (optional — rule-based fallback included) |
-| **Deployment** | Render (backend) + Netlify (frontend) |
 
 ---
 
@@ -155,8 +154,6 @@ cashclock/
 │   └── postcss.config.js
 │
 ├── datasets/                   # Raw SME dataset files
-├── netlify.toml                # Netlify deployment config
-├── render.yaml                 # Render backend deployment config
 └── README.md
 ```
 

From ba89e469f4c9a7e7007fbc296c33926fca6a3b1d Mon Sep 17 00:00:00 2001
From: anshul23102 <anshul23102@iiitd.ac.in>
Date: Sun, 12 Apr 2026 23:28:30 +0530
Subject: [PATCH 8/8] docs: rewrite README to meet NatWest hackathon submission
 guidelines
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Full rewrite of README.md with:
- Concise overview (what, problem, users) per guideline §1.1.i
- Features section — only implemented/working features per §4
- Explicit local-only setup instructions (Step 1–4) per §1.1.iii
- Troubleshooting table for common setup issues
- Tech stack with skillicons badges and tables per §1.1.iv
- Usage examples with API call sample per §1.1.v
- Full API reference table
- Architecture section with ASCII diagram and data flow per §6
- Technical depth: why Holt-Winters and rolling z-score per §6
- Limitations clearly labelled per §1.1.vi
- Future improvements clearly labelled as not yet implemented per §4
- License and DCO compliance section per §7
- Styled header/footer matching personal README aesthetic
---
 README.md | 378 ++++++++++++++++++++++++++++++++----------------------
 1 file changed, 226 insertions(+), 152 deletions(-)

diff --git a/README.md b/README.md
index 15b900c..9d694ce 100644
--- a/README.md
+++ b/README.md
@@ -4,11 +4,12 @@
 
 <div align="center">
 
-[![NatWest Hackathon](https://img.shields.io/badge/NatWest-Code%20for%20Purpose%20India%20Hackathon-purple?style=for-the-badge)](https://github.com/anshul23102/cashclock)
+[![NatWest Hackathon](https://img.shields.io/badge/NatWest-Code%20for%20Purpose%20India%20Hackathon-7B2FBE?style=for-the-badge&logo=data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHZpZXdCb3g9IjAgMCAyNCAyNCI+PC9zdmc+)](https://github.com/anshul23102/cashclock)
 [![License: Apache 2.0](https://img.shields.io/badge/License-Apache%202.0-blue?style=for-the-badge)](LICENSE)
 [![Python](https://img.shields.io/badge/Python-3.10+-3776AB?style=for-the-badge&logo=python&logoColor=white)](https://python.org)
 [![React](https://img.shields.io/badge/React-18-61DAFB?style=for-the-badge&logo=react&logoColor=black)](https://react.dev)
 [![FastAPI](https://img.shields.io/badge/FastAPI-009688?style=for-the-badge&logo=fastapi&logoColor=white)](https://fastapi.tiangolo.com)
+[![DCO Compliant](https://img.shields.io/badge/DCO-Compliant-green?style=for-the-badge)](https://developercertificate.org)
 
 </div>
 
@@ -16,52 +17,52 @@
 
 ## 🙋‍♂️ Overview
 
-**CashClock** is a full-stack web application that gives Indian small and medium enterprises (SMEs) real-time visibility into their cash position — and early warning of when they might run out of money. It uses statistical forecasting and AI-generated insights to predict cash flow 30 days ahead, detect anomalies in transactions, and surface pre-approved loan offers to businesses at risk of a cash crisis.
+**CashClock** is a full-stack web application that gives Indian small and medium enterprises (SMEs) real-time visibility into their cash position — and early warning of when they might run out of money. It uses **Holt-Winters statistical forecasting** and **Claude AI** to predict cash flow 30 days ahead, detect anomalies in transactions, and surface pre-approved loan offers to businesses at risk of a cash crisis.
 
-The platform serves two types of users: **business owners**, who see a personalised dashboard of their cash health, forecast, and loan options; and **bank managers**, who see a portfolio-wide view of all SME clients with risk classification, lending pipeline, and approval tools.
+The platform serves two types of users: **business owners**, who see a personalised dashboard of their cash health, forecast, anomalies, and loan options; and **bank managers**, who see a portfolio-wide view of all SME clients with risk classification, lending pipeline, and approval tools. The AI component is optional — the app falls back to rule-based summaries if no API key is configured, so it runs fully offline.
+
+> **Hackathon:** NatWest Group — Code for Purpose India Hackathon  
+> **Problem it solves:** Most Indian SMEs lack the financial tooling to anticipate cash shortfalls. CashClock gives them the same forecasting capability that large enterprises pay enterprise software for — at zero cost.
 
 ---
 
 ## ✅ Features
 
+> All features listed below are implemented and functional in the current codebase.
+
 ### 📊 Business Owner Dashboard
 
-| Feature | Description |
-|---|---|
-| 📈 **30-day cash forecast** | Three confidence paths — likely / optimistic / pessimistic |
-| 🚫 **No-Cash Zone detection** | Identifies future dates when balance falls below ₹15,000 |
-| 💰 **Balance tracker** | Week-over-week trend and percentage change |
-| 📉 **Forecast minimum** | Shows lowest projected balance and when it occurs |
-| 📅 **Daily cash calendar** | Colour-coded calendar showing each day's cash health |
-| ⚠️ **Anomaly feed** | Unusual transactions with severity, cause, and action |
-| 🔧 **What-if scenarios** | Model revenue changes (±50%) or one-off injections |
-| 🤖 **AI Ask Box** | Free-text Q&A powered by Claude AI |
-| 📄 **PDF report** | Multi-page formal business report with forecast charts |
-| 🏦 **Loan application** | In-app loan application for at-risk businesses |
+- **30-day cash flow forecast** — three confidence paths (likely / optimistic / pessimistic) using Holt-Winters Exponential Smoothing
+- **No-Cash Zone detection** — automatically identifies future dates when projected balance drops below ₹15,000
+- **Balance tracker** — week-over-week trend with percentage change
+- **Forecast minimum** — shows the lowest projected balance and the exact date it occurs
+- **Daily cash calendar** — colour-coded calendar (green / yellow / red) showing each day's cash health
+- **Anomaly feed** — unusual transactions flagged with severity (warning / high / critical), probable cause, and a suggested action
+- **What-if scenario builder** — model a revenue change (±50%) or a one-off cash injection, with live chart update showing impact vs baseline
+- **AI Ask Box** — free-text Q&A answered by Claude AI (falls back to rule-based response if no API key)
+- **PDF report download** — multi-page formal business report including forecast chart, anomaly summary, and health score
+- **In-app loan application** — business owners can apply for a pre-approved loan directly from the dashboard
 
 ### 🏦 Bank Manager Dashboard
 
-| Feature | Description |
-|---|---|
-| 🗂️ **Portfolio overview** | Total clients, at-risk count, pre-approved count, accepted rate |
-| 📊 **Risk distribution** | Healthy / watch / urgent / declining breakdown with counts |
-| 🥧 **Industry pie chart** | Distribution across all SME clients |
-| 📉 **Health score histogram** | Distribution of runway scores across portfolio |
-| 🔄 **Loan pipeline funnel** | Tracks offer sent → applied → approved → accepted |
-| 📆 **Forecasted dip timeline** | Which businesses will hit a cash crisis and when |
-| 🔍 **Business list** | Search + filter by industry and risk level |
-| 📨 **Bulk loan offers** | Send pre-approved offers to all at-risk businesses |
+- **Portfolio overview** — total clients, at-risk count, pre-approved count, and accepted-offer rate as KPI cards
+- **Risk distribution panel** — healthy / watch / urgent / declining breakdown with counts and colour coding
+- **Industry distribution pie chart** — breakdown of portfolio across SME sectors
+- **Health score histogram** — distribution of runway scores (0–100) across all businesses
+- **Loan pipeline funnel** — tracks offer sent → applied → approved → accepted
+- **Forecasted dip timeline** — which businesses will hit a cash crisis and when
+- **Business list with search and filter** — search by name, filter by industry and risk level
+- **Bulk loan offer dispatch** — send pre-approved offers to all at-risk businesses with one click
+- **Per-business detail view** — manager can drill into any business, see its full forecast, and manually approve a loan
 
 ### 🤖 AI & Analytics Engine
 
-| Feature | Description |
-|---|---|
-| 📐 **Holt-Winters ETS** | Exponential smoothing with weekly aggregation → daily distribution |
-| 📏 **Rolling z-score detection** | Anomaly severity classification — warning / high / critical |
-| 🏃 **Runway score (0–100)** | Combines balance coverage, trend, volatility, and dip severity |
-| 🎯 **Dynamic thresholds** | Per-business calibration from each business's own history |
-| 💬 **Claude AI integration** | Plain-English summaries with rule-based fallback |
-| 💳 **Loan risk scoring** | Three risk tiers (low / medium / high) affecting interest rate |
+- **Holt-Winters ETS forecasting** — triple exponential smoothing with weekly aggregation and day-of-week redistribution
+- **Rolling z-score anomaly detection** — severity classification relative to each business's own baseline, not a fixed threshold
+- **Runway score (0–100)** — composite score combining balance coverage, trend direction, volatility, and dip severity
+- **Dynamic per-business thresholds** — calibrated from each business's own 365-day transaction history
+- **Claude AI integration** — plain-English summaries and free-text Q&A via `claude-haiku-4-5`
+- **Loan risk scoring** — three tiers (low / medium / high) that determine interest rate and loan size
 
 ---
 
@@ -77,9 +78,9 @@ The platform serves two types of users: **business owners**, who see a personali
 | **Web Framework** | FastAPI + Uvicorn |
 | **Forecasting** | statsmodels (Holt-Winters Exponential Smoothing) |
 | **Data Processing** | pandas, numpy |
-| **AI / LLM** | Anthropic Claude API (`claude-haiku-4-5`) |
+| **AI / LLM** | Anthropic Claude API (`claude-haiku-4-5`) — optional |
 | **PDF Generation** | ReportLab |
-| **Database** | SQLite (via Python `sqlite3`) |
+| **Database** | SQLite (Python built-in `sqlite3`) |
 | **Config** | python-dotenv |
 
 **Frontend**
@@ -102,8 +103,9 @@ The platform serves two types of users: **business owners**, who see a personali
 
 | Category | Detail |
 |---|---|
-| **Database** | SQLite file (local, no external DB required) |
+| **Database** | SQLite file — no external database required |
 | **AI API** | Anthropic Claude API (optional — rule-based fallback included) |
+| **Environment** | Runs fully on `localhost` — no cloud account needed |
 
 ---
 
@@ -116,21 +118,21 @@ cashclock/
 │   ├── forecaster.py           # Holt-Winters 30-day cash flow forecast
 │   ├── anomaly.py              # Rolling z-score anomaly detection
 │   ├── health_insights.py      # Runway score and health classification
-│   ├── ai_coach.py             # Claude AI summaries and Q&A
-│   ├── loan.py                 # Loan sizing, risk scoring, repayment
+│   ├── ai_coach.py             # Claude AI summaries and free-text Q&A
+│   ├── loan.py                 # Loan sizing, risk scoring, repayment schedule
 │   ├── pdf_report.py           # ReportLab PDF report generation
-│   ├── database.py             # SQLite schema and queries
-│   ├── data_generator.py       # Realistic SME data generation
-│   ├── generate_sample.py      # Script to seed the database
+│   ├── database.py             # SQLite schema creation and queries
+│   ├── data_generator.py       # Realistic SME transaction data generator
+│   ├── generate_sample.py      # Script to seed the database with sample data
+│   ├── seed_data.sql           # Pre-generated SQL seed data (10 SME businesses)
 │   ├── requirements.txt        # Python dependencies
-│   ├── .env.example            # Environment variable template
-│   └── seed_data.sql           # Pre-generated SQL seed data
+│   └── .env.example            # Environment variable template
 │
 ├── frontend/                   # React + Vite web application
 │   ├── src/
 │   │   ├── App.jsx             # Root component and routing
 │   │   ├── main.jsx            # Entry point
-│   │   ├── index.css           # Global styles (Tailwind)
+│   │   ├── index.css           # Global styles (Tailwind directives)
 │   │   └── components/
 │   │       ├── Landing.jsx                    # Role selection screen
 │   │       ├── Dashboard.jsx                  # Manager portfolio dashboard
@@ -140,20 +142,20 @@ cashclock/
 │   │       ├── LoanOfferPage.jsx              # Loan offer detail and application
 │   │       ├── LoanOfferCard.jsx              # Loan offer summary card
 │   │       ├── CashBalanceForecastChart.jsx   # 30-day forecast line chart
-│   │       ├── CashFlowBreakdownChart.jsx     # Monthly inflow/outflow bars
+│   │       ├── CashFlowBreakdownChart.jsx     # Monthly inflow/outflow bar chart
 │   │       ├── CashCalendar.jsx               # Daily colour-coded calendar
-│   │       ├── PatternDrivers.jsx             # Trend sparkline + seasonality
+│   │       ├── PatternDrivers.jsx             # Trend sparkline + seasonality bars
 │   │       ├── AnomalyBandMini.jsx            # Mini anomaly indicator
 │   │       ├── WhatIfPanel.jsx                # Scenario builder UI
 │   │       ├── TrainingProgress.jsx           # Loading animation screen
 │   │       ├── LoginPage.jsx                  # Login screen
 │   │       └── ChartLegendBaseline.jsx        # Chart legend component
 │   ├── package.json
-│   ├── vite.config.js          # Vite config with API proxy to :8000
+│   ├── vite.config.js          # Vite config — proxies /api/* to backend :8000
 │   ├── tailwind.config.js
 │   └── postcss.config.js
 │
-├── datasets/                   # Raw SME dataset files
+├── datasets/                   # Raw SME dataset files used for data generation
 └── README.md
 ```
 
@@ -161,16 +163,24 @@ cashclock/
 
 ## ⚙️ Installation & Setup
 
+> These instructions set up the project to run **entirely on your local machine**. No cloud accounts, no deployment needed.
+
 ### Prerequisites
 
-- Python **3.10 or higher** — [python.org](https://python.org)
-- Node.js **18 or higher** — [nodejs.org](https://nodejs.org)
-- `npm` (bundled with Node.js)
-- _(Optional)_ An Anthropic API key for AI-powered summaries
+Before you begin, make sure you have the following installed:
+
+| Tool | Minimum Version | Download |
+|---|---|---|
+| **Python** | 3.10 | [python.org](https://python.org) |
+| **Node.js** | 18 | [nodejs.org](https://nodejs.org) |
+| **npm** | bundled with Node.js | — |
+| **Git** | any recent version | [git-scm.com](https://git-scm.com) |
+
+An Anthropic API key is **optional**. The app works fully without it — it will use rule-based text summaries instead of AI-generated ones.
 
 ---
 
-### 1. Clone the repository
+### Step 1 — Clone the repository
 
 ```bash
 git clone https://github.com/anshul23102/cashclock.git
@@ -179,7 +189,7 @@ cd cashclock
 
 ---
 
-### 2. Set up the backend
+### Step 2 — Set up the backend
 
 ```bash
 cd backend
@@ -192,42 +202,54 @@ cd backend
 python3 -m venv venv
 source venv/bin/activate
 
-# Windows
+# Windows (Command Prompt)
 python -m venv venv
 venv\Scripts\activate
 ```
 
+You should see `(venv)` appear at the start of your terminal prompt.
+
 **Install Python dependencies:**
 
 ```bash
 pip install -r requirements.txt
 ```
 
+This installs FastAPI, statsmodels, pandas, ReportLab, anthropic, and all other dependencies.
+
 **Configure environment variables:**
 
 ```bash
 cp .env.example .env
 ```
 
-Open `.env` and add your Anthropic API key _(optional — the app works without it using rule-based fallbacks)_:
+Open the `.env` file in any text editor. If you have an Anthropic API key, paste it in:
 
 ```env
 ANTHROPIC_API_KEY=your_api_key_here
 ```
 
+If you do not have a key, leave the file as-is — the app will use rule-based fallbacks automatically.
+
 **Start the backend server:**
 
 ```bash
 uvicorn main:app --reload --port 8000
 ```
 
-The API will be available at `http://localhost:8000`.
+You should see output like:
+```
+INFO:     Uvicorn running on http://127.0.0.1:8000 (Press CTRL+C to quit)
+INFO:     Started reloader process
+```
+
+The backend API is now running at `http://localhost:8000`. Keep this terminal open.
 
 ---
 
-### 3. Set up the frontend
+### Step 3 — Set up the frontend
 
-Open a **new terminal** and from the project root:
+Open a **new terminal window** (keep the backend terminal running), then from the project root:
 
 ```bash
 cd frontend
@@ -235,18 +257,38 @@ npm install
 npm run dev
 ```
 
-The frontend will be available at `http://localhost:5173`.
+You should see:
+```
+  VITE v5.x.x  ready in XXX ms
 
-> The Vite dev server automatically proxies all `/api/*` requests to the backend on port 8000 — no manual CORS configuration needed.
+  ➜  Local:   http://localhost:5173/
+```
+
+> The Vite dev server automatically proxies all `/api/*` requests to the backend on port 8000. No CORS configuration or manual URL changes needed.
 
 ---
 
-### 4. Open the app
+### Step 4 — Open the app
+
+Navigate to **`http://localhost:5173`** in your browser.
+
+You will see the CashClock landing page with two role options:
+
+| Role | What you see |
+|---|---|
+| **I'm a Bank Manager** | Portfolio view of all 10 SME clients with KPIs, charts, and loan tools |
+| **I'm a Business Owner** | Business selector → personal dashboard with forecast, anomalies, and loan offer |
+
+---
 
-Navigate to `http://localhost:5173`. You will see the landing page with two options:
+### Troubleshooting
 
-- **I'm a Bank Manager** — portfolio view of all SME clients
-- **I'm a Business Owner** — select your business to see your personal dashboard
+| Problem | Fix |
+|---|---|
+| `ModuleNotFoundError` on backend start | Make sure your venv is activated — you should see `(venv)` in your prompt |
+| `npm install` fails | Check Node.js version: `node --version` must be 18+ |
+| Backend starts but frontend shows blank | Confirm backend is running on port 8000 and frontend on 5173 |
+| AI summaries say "rule-based fallback" | Either no API key is set, or the key in `.env` is invalid — this is expected behaviour |
 
 ---
 
@@ -256,14 +298,18 @@ Navigate to `http://localhost:5173`. You will see the landing page with two opti
 
 1. Click **"I'm a Business Owner"** on the landing page
 2. Select a business from the list (e.g. _Ravi Electronics_)
-3. The dashboard loads with current balance, 30-day forecast, no-cash zone warnings, and anomalies
+3. The dashboard loads with:
+   - Current balance and week-over-week change
+   - 30-day forecast chart with three confidence bands
+   - No-cash zone warnings (if any)
+   - Recent anomalies with severity labels
 
 ### Running a what-if scenario
 
-1. Open a business dashboard and scroll to **"What-If Scenario"**
+1. Open any business dashboard and scroll to **"What-If Scenario"**
 2. Drag the **Revenue Change** slider (e.g. to −30%)
-3. Optionally add a one-off income injection (e.g. ₹50,000)
-4. Click **"Run Scenario"** — the chart updates to show projected impact vs baseline
+3. Optionally enter a one-off cash injection (e.g. ₹50,000)
+4. Click **"Run Scenario"** — the forecast chart updates to show projected vs baseline
 
 ### Asking the AI coach
 
@@ -272,38 +318,26 @@ In the **"Ask Your Business Coach"** panel, type a plain-English question:
 ```
 "Why did my cash drop in February?"
 "When is my next predicted cash shortage?"
-"What's driving my expenses up?"
+"What's driving my expenses up this month?"
 ```
 
-### Manager: sending loan offers
+The response is generated by Claude AI if an API key is present, or by the rule-based engine otherwise.
 
-1. Log in as **Bank Manager**
-2. Click **"Send Offers to All At-Risk"** for bulk pre-approved offers
-3. Or expand any individual business and click **"Approve Loan"** to manually approve
+### Downloading a PDF report
 
----
+On any business dashboard, click **"Download Report"**. A multi-page PDF is generated and downloaded, containing:
+- Business summary and current health score
+- 30-day forecast chart (image embedded)
+- Anomaly table with severity and causes
+- Loan eligibility summary
 
-## 📡 API Reference
+### Manager: sending loan offers
 
-| Method | Endpoint | Description |
-|---|---|---|
-| `GET` | `/api/health` | Server health check |
-| `GET` | `/api/businesses` | List all businesses with summary stats |
-| `GET` | `/api/businesses/{id}` | Full business data + 365 days of transactions |
-| `GET` | `/api/businesses/{id}/forecast` | 30-day forecast, health score, anomaly summary |
-| `GET` | `/api/businesses/{id}/anomalies` | Detailed anomaly report with z-scores |
-| `GET` | `/api/businesses/{id}/breakdown` | Monthly cash flow + expense composition |
-| `POST` | `/api/businesses/{id}/scenario` | What-if scenario analysis |
-| `POST` | `/api/businesses/{id}/ask` | AI-powered Q&A |
-| `GET` | `/api/businesses/{id}/report/pdf` | Download PDF report |
-| `POST` | `/api/businesses/{id}/apply-loan` | Business submits loan application |
-| `POST` | `/api/businesses/{id}/approve-loan` | Manager approves loan |
-| `GET` | `/api/businesses/{id}/loan-status` | Check loan application status |
-| `GET` | `/api/portfolio/manager` | Full manager portfolio with KPIs |
-| `POST` | `/api/portfolio/send-offers` | Bulk send pre-approved loan offers |
-| `POST` | `/api/offer/accept` | Customer accepts a loan offer |
+1. Log in as **Bank Manager**
+2. On the dashboard, click **"Send Offers to All At-Risk"** to bulk-send pre-approved offers
+3. Or search for a specific business → expand it → click **"Approve Loan"** to approve individually
 
-**Example — get forecast:**
+### Example API call
 
 ```bash
 curl http://localhost:8000/api/businesses/1/forecast
@@ -325,46 +359,86 @@ curl http://localhost:8000/api/businesses/1/forecast
 
 ---
 
+## 📡 API Reference
+
+| Method | Endpoint | Description |
+|---|---|---|
+| `GET` | `/api/health` | Server health check |
+| `GET` | `/api/businesses` | List all businesses with summary stats |
+| `GET` | `/api/businesses/{id}` | Full business data + 365 days of transactions |
+| `GET` | `/api/businesses/{id}/forecast` | 30-day forecast, health score, anomaly summary |
+| `GET` | `/api/businesses/{id}/anomalies` | Detailed anomaly report with z-scores |
+| `GET` | `/api/businesses/{id}/breakdown` | Monthly cash flow + expense composition |
+| `POST` | `/api/businesses/{id}/scenario` | What-if scenario analysis |
+| `POST` | `/api/businesses/{id}/ask` | AI-powered free-text Q&A |
+| `GET` | `/api/businesses/{id}/report/pdf` | Download multi-page PDF report |
+| `POST` | `/api/businesses/{id}/apply-loan` | Business owner submits loan application |
+| `POST` | `/api/businesses/{id}/approve-loan` | Manager approves a loan |
+| `GET` | `/api/businesses/{id}/loan-status` | Poll current loan application status |
+| `GET` | `/api/portfolio/manager` | Full manager portfolio with all KPIs |
+| `POST` | `/api/portfolio/send-offers` | Bulk send pre-approved loan offers |
+| `POST` | `/api/offer/accept` | Business owner accepts a loan offer |
+
+---
+
 ## 🧠 Technical Depth
 
 ### Why Holt-Winters Exponential Smoothing?
 
-Indian SME cash flows are strongly seasonal — festivals, monsoon slowdowns, and quarterly tax cycles create recurring patterns. Holt-Winters (ETS) was chosen because it explicitly models **trend** and **seasonality** as first-class components. The model is trained on each business's own 365-day history, producing personalised forecasts rather than industry averages.
+Indian SME cash flows are strongly seasonal — festivals (Diwali, Holi), monsoon slowdowns, and quarterly GST cycles create recurring patterns that simpler models miss. **Holt-Winters Triple Exponential Smoothing (ETS)** was chosen because it explicitly models **level**, **trend**, and **seasonality** as separate components, producing personalised forecasts from each business's own 365-day history rather than industry averages.
 
-**Key detail:** Raw daily data is aggregated to weekly before fitting, reducing noise from zero-revenue weekends. The weekly forecast is redistributed back to daily using each business's observed day-of-week pattern.
+**Key engineering detail:** Raw daily data is aggregated to weekly before fitting, which removes noise from zero-revenue weekends and public holidays. The fitted weekly forecast is then redistributed back to daily values using each business's observed day-of-week pattern — preserving weekly cycle accuracy while giving granular daily output.
 
-### Why rolling z-score anomaly detection?
+### Why rolling z-score for anomaly detection?
 
-A fixed threshold fails for SMEs with vastly different scales. Rolling z-scores normalise against each business's own recent history — a spike that is 2.5σ above *that business's* baseline is flagged regardless of absolute rupee value.
+A fixed rupee threshold fails across SMEs with vastly different transaction scales — ₹50,000 is routine for one business and extraordinary for another. Rolling z-scores normalise each transaction against that business's own recent history window. A spike that is 2.5σ above *this business's* typical pattern is flagged regardless of absolute value, making the detector equally sensitive for a micro-SME and a mid-size manufacturer.
 
 ### System Architecture
 
 ```
-┌─────────────────────────────────────────────────────────┐
-│                      Browser (React)                     │
-│  Landing → Manager Dashboard / Business Owner Dashboard  │
-└───────────────────────┬─────────────────────────────────┘
-                        │  HTTP / REST (via Vite proxy)
-                        ▼
-┌─────────────────────────────────────────────────────────┐
-│                   FastAPI Backend (:8000)                │
-│                                                         │
-│  ┌─────────────┐  ┌──────────────┐  ┌───────────────┐  │
-│  │ forecaster  │  │   anomaly    │  │health_insights│  │
-│  │(Holt-Winters│  │(z-score det.)│  │(runway score) │  │
-│  └─────────────┘  └──────────────┘  └───────────────┘  │
-│                                                         │
-│  ┌─────────────┐  ┌──────────────┐  ┌───────────────┐  │
-│  │  ai_coach   │  │    loan      │  │  pdf_report   │  │
-│  │(Claude API) │  │(risk scoring)│  │  (ReportLab)  │  │
-│  └─────────────┘  └──────────────┘  └───────────────┘  │
-└───────────────────────┬─────────────────────────────────┘
-                        │
-               ┌────────▼────────┐       ┌──────────────────┐
-               │   SQLite DB     │       │  Anthropic API   │
-               │  (businesses +  │       │  (Claude Haiku)  │
-               │   daily_data)   │       │  [optional]      │
-               └─────────────────┘       └──────────────────┘
+┌──────────────────────────────────────────────────────────────┐
+│                      Browser (React 18)                       │
+│   Landing Page → Manager Dashboard / Business Dashboard       │
+│       Recharts · Tailwind CSS · Lucide Icons · Axios          │
+└───────────────────────────┬──────────────────────────────────┘
+                            │  HTTP / REST
+                            │  (Vite proxy: /api/* → :8000)
+                            ▼
+┌──────────────────────────────────────────────────────────────┐
+│                    FastAPI Backend (:8000)                     │
+│                                                              │
+│   ┌─────────────┐  ┌──────────────┐  ┌──────────────────┐   │
+│   │ forecaster  │  │   anomaly    │  │ health_insights   │   │
+│   │Holt-Winters │  │ rolling z-   │  │ runway score 0-  │   │
+│   │ETS, 30-day  │  │ score detect │  │ 100, classif.    │   │
+│   └─────────────┘  └──────────────┘  └──────────────────┘   │
+│                                                              │
+│   ┌─────────────┐  ┌──────────────┐  ┌──────────────────┐   │
+│   │  ai_coach   │  │     loan     │  │   pdf_report     │   │
+│   │ Claude API  │  │ risk scoring │  │   ReportLab      │   │
+│   │ + fallback  │  │ + repayment  │  │   multi-page     │   │
+│   └─────────────┘  └──────────────┘  └──────────────────┘   │
+└───────────────────────────┬──────────────────────────────────┘
+                            │
+             ┌──────────────┴──────────────┐
+             ▼                             ▼
+  ┌─────────────────────┐      ┌────────────────────┐
+  │      SQLite DB      │      │   Anthropic API    │
+  │  businesses table   │      │   claude-haiku-4-5 │
+  │  daily_data table   │      │   [optional]       │
+  └─────────────────────┘      └────────────────────┘
+```
+
+**Data flow for a forecast request:**
+```
+Browser GET /api/businesses/{id}/forecast
+  → main.py route handler
+  → database.py: fetch 365 days of daily_data
+  → forecaster.py: aggregate weekly → fit ETS → project 30 days → redistribute daily
+  → anomaly.py: compute rolling z-scores → classify severity
+  → health_insights.py: compute runway score → classify risk tier
+  → ai_coach.py: generate summary (Claude API or rule-based)
+  → JSON response → React renders charts
 ```
 
 ---
@@ -373,64 +447,64 @@ A fixed threshold fails for SMEs with vastly different scales. Rolling z-scores
 
 | Limitation | Detail |
 |---|---|
-| 🧪 **Simulated data** | 10 SME businesses generated from realistic statistical templates — not real bank data |
-| 🔐 **No authentication** | Simple role-selection screen without passwords or session management |
-| 🗃️ **SQLite only** | Not suitable for multi-user production; PostgreSQL needed for scale |
-| 🇮🇳 **India-only patterns** | All businesses modelled with INR, Indian seasonal events, Indian tax cycles |
-| 🔌 **No live bank feed** | Cash flow data is pre-loaded, not connected to live transaction APIs |
+| **Simulated data** | 10 SME businesses are generated from realistic statistical templates — not real bank transaction data |
+| **No authentication** | The role selection screen has no passwords or session management; anyone can switch roles |
+| **SQLite only** | The database is a local file; it is not designed for concurrent multi-user access |
+| **India-only patterns** | All businesses are modelled with INR, Indian seasonal events, and Indian tax cycles |
+| **No live bank feed** | Cash flow data is pre-loaded; the app is not connected to any live transaction API or account aggregator |
+| **Forecast accuracy** | ETS works well for the patterns in the generated data; accuracy on real-world data would require re-calibration |
 
 ---
 
 ## 🔮 Future Improvements
 
-- 🏦 **Open Banking integration** — connect to RBI account aggregator APIs for live data
-- 🔐 **User authentication** — secure login with role-based access control
-- 🗄️ **PostgreSQL migration** — replace SQLite with a production-grade database
-- 📱 **Mobile app** — React Native client for on-the-go cash health monitoring
-- 🔔 **Push notifications** — alert business owners via SMS/email for no-cash zone predictions
-- 📆 **Longer forecast horizon** — extend from 30 to 90-day forecasts
+> These are features that would be built with more time — they are **not** currently implemented.
+
+- **Open Banking integration** — connect to RBI account aggregator APIs for live transaction data
+- **User authentication** — secure login with JWT tokens and role-based access control
+- **PostgreSQL migration** — replace SQLite with a production-grade database for multi-user scale
+- **Push notifications** — alert business owners via SMS or email when a no-cash zone is predicted
+- **90-day forecast horizon** — extend beyond the current 30-day window
+- **Mobile app** — React Native client for on-the-go cash health monitoring
 
 ---
 
-## 📁 Configuration
+## 📁 Configuration Reference
 
 | Variable | Required | Description |
 |---|---|---|
-| `ANTHROPIC_API_KEY` | Optional | Claude API key for AI summaries. If omitted, rule-based fallbacks are used. |
+| `ANTHROPIC_API_KEY` | Optional | Claude API key for AI summaries and Q&A. Omit for rule-based fallbacks. |
 
 ```bash
+# Copy the example file and edit it
 cp backend/.env.example backend/.env
 ```
 
-> **Security note:** Never commit your `.env` file. It is listed in `.gitignore`.
-
----
-
-## 🏆 Highlights
-
-| | |
-|---|---|
-| 🥇 NatWest Code for Purpose – India Hackathon | Submitted project |
-| 🤖 Claude AI Integration | Free-text Q&A + narrative summaries |
-| 📐 Holt-Winters Forecasting | 30-day personalised cash flow prediction |
-| 🇮🇳 India-focused | INR, Indian seasonal patterns, Indian SME data |
+> **Security:** Never commit your `.env` file. It is already in `.gitignore`. Only commit `.env.example` with placeholder values.
 
 ---
 
-## 📄 License
+## 📄 License & Compliance
 
-This project is submitted under the **Apache License 2.0**, in compliance with NatWest Group Code for Purpose – India Hackathon requirements.
+This project is submitted under the **Apache License 2.0**, in compliance with NatWest Group Code for Purpose — India Hackathon requirements.
 
-All commits are DCO-compliant. Third-party libraries are used under their respective open-source licences (MIT, Apache 2.0, BSD).
+- All commits are **DCO-compliant** (Developer Certificate of Origin)
+- A single email address (`anshul23102@iiitd.ac.in`) is used for all commits and hackathon communication
+- All third-party libraries are used under their respective open-source licences (MIT, Apache 2.0, BSD-3)
+- No confidential, proprietary, or real customer data is included in this repository
+- No API keys, passwords, or secrets are hard-coded anywhere in the codebase
 
 ---
 
 <div align="center">
 
-Built with ❤️ for the **NatWest Group Code for Purpose – India Hackathon**
+Built with ❤️ for the **NatWest Group Code for Purpose — India Hackathon**
 
 *Helping Indian SMEs see their financial future clearly.*
 
+[![Portfolio](https://img.shields.io/badge/Author-Anshul%20Jain-7B2FBE?style=for-the-badge&logo=github&logoColor=white)](https://github.com/anshul23102)
+[![Email](https://img.shields.io/badge/Email-anshul23102%40iiitd.ac.in-D14836?style=for-the-badge&logo=gmail&logoColor=white)](mailto:anshul23102@iiitd.ac.in)
+
 <img src="https://capsule-render.vercel.app/api?type=waving&color=gradient&customColorList=6,11,20&height=100&section=footer"/>
 
 </div>