Aura

Your Local AI Sales Agent
Autonomous lead generation, outreach, and deal closing — running entirely on your desktop.

Quick Start · Features · Architecture · Technical Docs · User Manual

What is Aura?

Aura is a desktop AI sales agent that automates the entire B2B lead generation pipeline — from finding prospects to closing deals. It runs locally on your machine with a fleet of 20 specialized AI agents that handle prospecting, research, outreach, follow-ups, invoicing, and even voice calls.

Unlike cloud SaaS tools, Aura keeps your data local (SQLite), your API keys encrypted (machine-bound AES), and gives you full control over autonomy levels — from observer mode to full autopilot.

The Pipeline

Find leads → Enrich & qualify → Deep research → Draft personalized emails
    → Send sequences → Detect replies → Classify intent → Handle objections
        → Follow up → Close deal    (or)    → Voice call as last resort

Every step is automated. Every step is configurable. Every step requires your approval until you say otherwise.

Quick Start

Install the CLI

# Install from source (recommended)
git clone https://github.com/Etriti00/aura-app.git
cd aura-app
pip install .

# Or install in editable/dev mode
pip install -e .

# Install the browser engine (needed for web scraping)
playwright install chromium

After installation, the aura command is available globally:

$ aura status
Aura v2.1.0 — System Status
───────────────────────────────
  Campaigns          0
  Leads              0
  Agents             20

$ aura help
$ aura hunt "plumber" --city "Austin TX"
$ aura                    # starts interactive REPL

Install the Desktop App (GUI)

# Option A: Download pre-built executable
# → https://github.com/Etriti00/aura-app/releases
#   Windows: Aura.exe  |  macOS: Aura.app  |  Linux: ./Aura

# Option B: Install from source with GUI
git clone https://github.com/Etriti00/aura-app.git
cd aura-app
pip install ".[gui]"
playwright install chromium
aura-gui

Cross-Platform Notes

Platform	CLI Install	GUI Install	Build
Windows	`pip install .` → `aura`	`pip install ".[gui]"` → `aura-gui`	`pyinstaller aura.spec` → `dist\Aura\Aura.exe`
macOS	`pip install .` → `aura`	`pip install ".[gui]"` → `aura-gui`	`pyinstaller aura.spec` → `dist/Aura.app`
Linux	`pip install .` → `aura`	`pip install ".[gui]"` → `aura-gui`	`pyinstaller aura.spec` → `dist/Aura/Aura`

Prerequisites: Python 3.10+ and Git.

First Launch

On first launch, configure at least one AI API key:

# CLI
aura config-api-keys

# GUI
# The Setup Wizard opens automatically on first run

AI Provider Key — Anthropic (Claude), OpenAI, or Google (Gemini)
Sender Identity — aura config-set sender_name "Your Name"
Email Delivery — aura config-smtp

All API keys are encrypted with machine-bound AES-256. They never leave your device.

Features

Lead Discovery & Enrichment

Multi-source scraping — DuckDuckGo, Google Maps, Yelp
API integrations — Apollo.io, Hunter.io, HubSpot CRM
CSV imports — LinkedIn Sales Navigator exports, batch files
Auto-enrichment — Email finder, phone lookup, website analysis
AI qualification — Automatic lead scoring with LLM-powered assessment

Deep Research

Multi-provider intelligence — Tavily, Firecrawl, Apify
LLM synthesis — Generates company overview, pain points, tech stack, gaps & opportunities
Auto-depth selection — Quick research for low-score leads, deep dive for high-potential

Outreach Automation

Research-powered emails — Drafts reference actual company data, competitor gaps, and pain points
Multi-step sequences — Automated follow-up cadences with customizable delays
Reply detection — IMAP polling classifies intent (interested, objection, not interested, question, unsubscribe)
Conversation engine — Multi-turn thread management with objection handling
A/B testing — Compare subject lines and email variants

AI Agent Fleet

20 specialized agents — Prospector, Qualifier, Closer, Researcher, Accountant, Caller, and more
Rank-based hierarchy — Commander (C-Level) → Specialists → Workers
Task routing — 25+ task types automatically dispatched to the right specialist
Ticket system — Kanban board with escalation, dependencies, and due dates
Self-improvement — Agents learn from performance metrics and reflection scores

Voice Calling (Last Resort)

Twilio integration — WebSocket media streams for real-time audio
TTS cascade — ElevenLabs → OpenAI → Piper (local fallback)
STT — Whisper (local or API)
Auto-trigger — Detects stalled leads (3+ failed emails or 7+ days silent)
Always requires approval — Even at full-trust autonomy level

Security & Reliability

Per-install encryption salt — Unique random salt per installation (auto-migrates from legacy)
Key migration — Automatic re-encryption of legacy ciphertext to new per-install salt
LLM retry with backoff — Exponential backoff on transient errors (429, 503, timeouts)
Thread-safe database — Serialized writes prevent SQLite locking errors
Thread-safe delivery counter — Atomic daily send limit with threading.Lock
Browser lifecycle management — Context-managed Playwright with batch mode and stealth for bulk operations
IMAP connection pooling — Persistent connections with automatic stale detection and reconnect
Resource cleanup on error — SMTP and IMAP connections always closed via try/finally
HTML injection prevention — Email body escaped before HTML embedding
Database indexes — 15 indexes on frequently queried columns for faster lookups
Graceful shutdown — closeEvent stops all timers, fleet, gateways, and batch browser on exit
GPU-aware scheduling — Ollama calls serialized via semaphore for single-GPU machines
Thread-safe safety guard — All mutable counters protected by locks

Autonomy & Control

4 autonomy levels — Observer, Supervised, Autonomous, Full Trust
Approval queue — Review and approve/deny any action before execution
Budget controls — Daily spend limits with automatic tier downgrade
Rate limiting — Per-provider API queues prevent throttling

Integrations

Telegram bot — Control Aura from Telegram with natural language commands
Discord bot — Same capabilities via Discord server
Command palette — Ctrl+K fuzzy search across all 14 pages
Cross-page navigation — Deep links between pages with context passing

Analytics & Intelligence

Dashboard — Real-time campaign stats, funnel visualization, conversion rates
Trends — Google Trends integration for market intelligence
Budget tracking — Per-model cost breakdown, daily/monthly projections
Command history — Full audit trail with tree visualization

CLI Reference

The CLI provides 81 commands across 17 groups with full feature parity to the GUI. Run aura to start the interactive REPL, or aura <command> for one-shot execution.

REPL Mode

$ aura
Aura v2.1.0 — AI Sales Agent
Type /help for commands, or type naturally.

aura> /hunt plumber --city "Austin TX" --limit 20
aura> /qualify 1
aura> /draft 1
aura> /send 1
aura> find me SaaS leads in healthcare    ← natural language works too

Command Groups

Group	Commands	Description
Pipeline	`/hunt`, `/qualify`, `/enrich`, `/draft`, `/send`, `/replies`, `/sequence`	Core lead-to-email pipeline
Campaigns	`/campaigns`, `/campaign-create`, `/campaign-status`, `/campaign-pause`, `/campaign-resume`, `/export-csv`, `/export-pdf`	Campaign management and export
Leads	`/leads`, `/lead-detail`, `/lead-lifecycle`, `/lead-search`, `/case`	Lead management and case files
Fleet	`/fleet-status`, `/fleet-boot`, `/fleet-shutdown`, `/agents`, `/agent-assign`, `/goals`, `/goal-create`, `/reflections`, `/knowledge-graph`, `/conversations`, `/ask`, `/improvement`	AI agent fleet operations
Kanban	`/tickets`, `/ticket-create`, `/ticket-update`, `/ticket-comment`, `/ticket-stats`	Ticket/task management
Skills	`/skills`, `/skill-detail`	AI skill registry
Research	`/research`, `/research-report`, `/research-queue`	Lead research intelligence
Voice	`/call`, `/call-log`, `/call-transcript`	Voice call management
Budget	`/budget`, `/budget-set`, `/token-usage`	Cost pacing and token tracking
Trends	`/trends`, `/trends-opportunities`, `/trends-alerts`	Google Trends market intelligence
Autonomy	`/autonomy-level`, `/autonomy-set`, `/approvals`, `/approve`, `/deny`	Agent autonomy controls
Suppression	`/suppression-list`, `/suppress`, `/unsuppress`	Email suppression management
Integrations	`/gateway-status`, `/gateway-connect`, `/gateway-disconnect`, `/crm-sync`, `/gateway-auth`	Telegram, Discord, CRM
History	`/history`, `/history-detail`, `/history-tree`	Command audit trail
Config	`/config`, `/config-set`, `/config-api-keys`, `/config-smtp`	Settings management
Knowledge	`/knowledge-add`, `/knowledge-list`, `/knowledge-remove`, `/memory-rules`, `/memory-stats`, `/memory-clear`	Knowledge base & correction memory
System	`/help`, `/status`, `/version`, `/clear`, `/exit`	System utilities

One-Shot Commands

# Hunt leads
aura hunt "SaaS companies" --city "San Francisco" --limit 100

# Check campaign stats
aura campaign-status 1

# Show system status
aura status

# Get help
aura help pipeline

# Verbose mode (show engine logs)
aura --verbose status

Architecture

┌─────────────────────────────────────────────────────────┐
│              Interface Layer (GUI or CLI)                 │
│   GUI: PySide6 (14 Pages, Chat Panel, Sidebar)          │
│   CLI: REPL + 75 commands (no PySide6 required)         │
├─────────────────────────────────────────────────────────┤
│                   Controller Layer                       │
│   GUI: 19 QObject controllers with Signal/Slot wiring   │
│   CLI: Direct engine calls (bypasses controllers)       │
├─────────────────────────────────────────────────────────┤
│                   Core Engine Layer                      │
│          50+ specialized engines (business logic)        │
├─────────────────────────────────────────────────────────┤
│                   Database Layer                         │
│       SQLAlchemy ORM  │  SQLite (WAL mode)  │  30+ tables│
├─────────────────────────────────────────────────────────┤
│                   External Services                      │
│  LiteLLM │ Apollo │ Twilio │ Telegram │ Discord │ IMAP   │
└─────────────────────────────────────────────────────────┘

Project Structure

aura-app/
├── main.py                  # GUI entry point
├── cli.py                   # CLI entry point (75 commands, REPL)
├── config.py                # All constants, paths, design tokens
├── aura.spec                # PyInstaller build configuration (cross-platform)
├── pyproject.toml           # Python packaging (pip install -e .)
├── requirements.txt         # Full dependencies (GUI + CLI)
├── requirements-cli.txt     # CLI-only dependencies (no PySide6)
│
├── core/                    # 50+ business logic engines
│   ├── ai_engine.py         # LLM orchestration (generate, qualify, classify)
│   ├── agent_engine.py      # Agent task execution with context building
│   ├── fleet_orchestrator.py # Multi-agent dispatch and coordination
│   ├── orchestrator_engine.py # Natural language command → action mapping
│   ├── scraper_engine.py    # Multi-source web scraping
│   ├── delivery_engine.py   # Email delivery (Resend + SMTP)
│   ├── research_engine.py   # Multi-provider research orchestration
│   ├── voice_call_engine.py # Twilio WebSocket voice calling
│   ├── router_engine.py     # 4-tier LLM routing (local→ollama→haiku→sonnet)
│   ├── rag_engine.py        # TF-IDF + optional ChromaDB retrieval
│   ├── voice/               # TTS (ElevenLabs, OpenAI, Piper) + STT (Whisper)
│   ├── gateway_adapters/    # Telegram + Discord bot adapters
│   ├── enrichment_layers/   # DNS, Ollama, free APIs, deep crawl enrichment
│   └── ...                  # 40+ more engines
│
├── controllers/             # 19 signal-based UI controllers
│   ├── hunter_controller.py
│   ├── outreach_controller.py
│   ├── fleet_controller.py
│   ├── autonomy_controller.py
│   └── ...
│
├── ui/
│   ├── main_window.py       # Application shell + engine wiring
│   ├── setup_wizard.py      # First-run configuration
│   ├── pages/               # 14 full-page views
│   │   ├── dashboard.py     # Campaign analytics
│   │   ├── hunter.py        # Lead discovery
│   │   ├── forge.py         # AI persona management
│   │   ├── outreach.py      # Email campaigns
│   │   ├── fleet.py         # Agent monitoring
│   │   ├── kanban.py        # Task board
│   │   ├── research.py      # Research reports
│   │   ├── calls.py         # Voice call management
│   │   └── ...              # 6 more pages
│   └── components/          # Reusable widgets
│       ├── sidebar.py
│       ├── chat_panel.py
│       ├── command_palette.py
│       └── ...
│
├── database/
│   ├── schema.py            # 50+ SQLAlchemy models
│   ├── db_manager.py        # Session factory, WAL mode, thread-safe writes
│   ├── migrations.py        # ALTER TABLE migrations for backward compat
│   ├── seed_agents.py       # 20 agent definitions + hierarchy setup
│   └── seed_skills.py       # Built-in skill & settings seeding
│
├── assets/
│   ├── themes/              # QSS stylesheets (dark + light)
│   ├── icons/               # Application icon
│   └── templates/           # CSV import templates
│
├── scripts/                 # Build scripts (cross-platform, macOS icon, Linux installer)
│   ├── build.py             # Cross-platform build automation
│   ├── build_icns.sh        # macOS icon generation
│   └── linux/               # Linux desktop entry + installer
│
└── tests/                   # 1250+ tests across 50+ files
    ├── conftest.py          # Fixtures (in-memory DB, QApp)
    └── test_*.py            # Comprehensive coverage

Key Technologies

Component	Technology
Desktop Framework	PySide6 (Qt 6)
Database	SQLAlchemy + SQLite (WAL mode)
LLM Routing	LiteLLM (Anthropic, OpenAI, Google, Ollama)
Email Delivery	Resend API + SMTP fallback
Web Scraping	Playwright + BeautifulSoup
Voice Calls	Twilio + WebSocket media streams
TTS	ElevenLabs, OpenAI, Piper (local)
STT	Whisper (local via faster-whisper, or API)
Encryption	AES-256 via `cryptography` (machine-bound, per-install salt)
CLI	75 commands, REPL, natural language fallback
Packaging	PyInstaller (OneDir), cross-platform (Win/macOS/Linux)

Configuration

All configuration lives in config.py. Key settings you may want to adjust:

Setting	Default	Description
`MAX_DAILY_EMAILS`	100	Daily outbound email limit
`FOLLOWUP_CHECK_INTERVAL_MS`	1,800,000	Follow-up sequence check interval (30 min)
`REPLY_CHECK_INTERVAL_MS`	7,200,000	IMAP reply check interval (2 hours)
`ESCALATION_CHECK_INTERVAL_MS`	300,000	Ticket escalation check (5 min)
`AGENT_CONTEXT_MAX_TOKENS`	8,000	Max context tokens per agent task
`CALLER_FAILED_EMAIL_THRESHOLD`	3	Failed emails before voice call eligibility
`CALLER_STALLED_DAYS`	7	Days silent before stalled-lead detection

Runtime settings (API keys, toggles, sender identity) are configured in the Settings page within the app.

Building from Source

Windows

venv\Scripts\activate
pyinstaller aura.spec --noconfirm
# Output: dist/Aura/Aura.exe

macOS

source venv/bin/activate
# Generate .icns icon (optional, requires iconutil)
bash scripts/build_icns.sh
# Build
pyinstaller aura.spec --noconfirm
# Output: dist/Aura.app

Linux

source venv/bin/activate
pyinstaller aura.spec --noconfirm
# Output: dist/Aura/Aura

# Optional: System-wide install
sudo bash scripts/linux/install.sh

Cross-Platform Build Script

python scripts/build.py

The build bundles all assets, themes, fonts, and dependencies into a self-contained directory.

Testing

# Run full test suite
venv\Scripts\python.exe -m pytest tests/ -v --tb=long

# Run a specific test file
venv\Scripts\python.exe -m pytest tests/test_agent_engine.py -v

# Run tests matching a pattern
venv\Scripts\python.exe -m pytest tests/ -k "test_stalled" -v

Current status: 1250+ tests across 50+ files — 100% passing.

Documentation

Document	Description
Technical Documentation	Architecture deep-dive, engine reference, database schema, security model
User Manual	Page-by-page walkthrough, feature toggles, keyboard shortcuts, troubleshooting

Supported AI Providers

Aura works with any combination of these LLM providers:

Provider	Models	Use Case
Anthropic	Claude Haiku, Sonnet	Primary (recommended)
OpenAI	GPT-4o, GPT-4o-mini	Alternative
Google	Gemini Pro, Flash	Alternative
Ollama	Any local model	Privacy-first, free tier

The 4-tier router automatically selects the optimal model based on task complexity and budget:

Tier 1 (Local)  →  Tier 2 (Haiku/Flash)  →  Tier 3 (Sonnet/GPT-4o)  →  Tier 4 (Opus)
   Free              ~$0.001/task              ~$0.01/task               ~$0.10/task

Budget pacing automatically downgrades tiers when daily spend approaches limits.

Contributing

Contributions are welcome. To get started:

Fork the repository
Create a feature branch (git checkout -b feature/your-feature)
Make your changes
Run the test suite (pytest tests/ -v)
Commit (git commit -m "Add your feature")
Push (git push origin feature/your-feature)
Open a Pull Request

Please ensure all tests pass before submitting.

Changelog

v2.1.0 — Intelligence & Audit Hardening

Correction Memory Engine — Detects user corrections ("no, I meant X") and learns rules that persist across conversations. Agents automatically inject learned rules into their context
Knowledge Base Engine — Store and retrieve business knowledge entries (products, competitors, pricing, processes). New Settings tab for managing entries with search
Per-Agent Auto-Memory — Each agent automatically stores and retrieves learned behaviors in per-agent memory logs, injected into agent context during task execution
Knowledge CLI commands — /knowledge-add, /knowledge-list, /knowledge-remove, /memory-rules, /memory-stats, /memory-clear
Audit fixes — Fixed CLI /enrich crash (int→dict), gateway platform hardcoding, Telegram key mismatch, GMaps API key decryption, missing orchestrator intents, Whisper temp file leak
Missing PyInstaller imports — Added skill_registry, hubspot_engine, linkedin_engine, icons, command_palette to aura.spec
Version: 2.0.0 → 2.1.0 across config.py, pyproject.toml, aura.spec
Tests: 1200 → 1250+ tests (50+ new tests across 2 new test files)

v2.0.0 — Enterprise Features + Settings Overhaul

Multi-platform response formatting — ResponseFormatter renders agent output for Telegram (HTML), Discord (Markdown), Chat (rich text), and CLI (plain text)
4-layer enrichment pipeline — DNS/WHOIS (Layer 0), Ollama local LLM (Layer 1), free APIs (Layer 2), deep web crawl (Layer 4) with weighted completeness scoring
Excel export engine — Professional .xlsx exports with multiple sheets (summary, leads, agents, timeline), auto-column-width, styled headers, and charts
Pricing + invoice system — Service CRUD, invoice generation (PDF via ReportLab or text fallback), approval flow with rank-based escalation, revenue summaries. New Accountant agent (20th agent)
Discord server mode — Auto-create notification channels (#leads, #campaigns, #fleet, #alerts, #reports), event→channel routing with embeds, config persistence
Telegram command system — 12 slash commands (/status, /hunt, /leads, /agents, /draft, /send, /campaigns, /budget, /approve, /deny, /help, /settings) with inline keyboards
Business & Invoicing settings — New Settings tab with company info, banking details, and invoice configuration (16 fields for agent context and invoice generation)
Tabbed Settings page — Restructured from single scroll into 6 sub-tabs: API Keys, AI Config, Email & Delivery, Features, Business & Invoicing, Appearance
Schema expansion — 5 new models (Service, Invoice, InvoiceLineItem, FinanceNote, DiscordServerConfig), expanded Lead/EnrichmentData/Settings
Tests: 959 → 1200 tests (241 new tests across 8 new test files)

v1.3.0 — Advanced CLI + Cross-Platform

Advanced CLI: Complete rewrite of cli.py — 75 commands across 16 groups with full GUI parity
Easy install: pip install . → aura command available globally (CLI-only, no PySide6 required)
GUI as optional: pip install ".[gui]" → includes PySide6 for desktop app
Clean output: Zero noise by default — no warnings, no INFO logs. Use --verbose for debug output
REPL mode: Interactive aura> prompt with /help system, fuzzy command matching, ANSI formatting
Natural language: Type plain English in the REPL — orchestrator parses intent and executes
One-shot mode: aura hunt "plumber" --city "Austin TX" runs a single command and exits
Full engine init: CLI initializes all 50+ engines (mirrors main_window.py exactly)
Cross-platform: Platform-aware aura.spec (Windows .exe, macOS .app bundle, Linux executable)
macOS icon: scripts/build_icns.sh generates .icns from PNG
Linux installer: scripts/linux/install.sh + .desktop file for system-wide install
Build script: scripts/build.py cross-platform build automation
CI/CD: GitHub Actions matrix build for Windows, macOS, and Linux
PySide6-optional: navigation_service.py and thread_worker.py work without Qt

v1.2.0 — Audit Round 2: Deep Hardening

Key migration: KeyVault.migrate_ciphertext() re-encrypts legacy-salt keys with new per-install salt on startup
Batch browser wiring: Hunter controller now calls start_batch()/end_batch() around enrichment loops
Stealth in batch path: playwright_stealth applied to batch browser pages (not just single-page mode)
Thread-safe delivery: DeliveryEngine daily counter uses threading.Lock with atomic _increment_daily()
SMTP leak fix: All SMTP connections wrapped in try/finally with server.quit()
HTML escape: Email body HTML-escaped before embedding to prevent XSS injection
IMAP leak fix: Triage engine IMAP connections wrapped in try/finally with mail.logout()
Database indexes: 15 indexes on frequently queried columns (leads, agent_tasks, tickets, command_log)
Graceful shutdown: MainWindow.closeEvent() stops timers, fleet, IMAP, gateways, batch browser, voice engine
Consolidated migrations: Removed dual migration system — all column migrations now in database/migrations.py
Tests: 935 → 959 tests (24 new audit round 2 hardening tests)

v1.1.0 — Hardening & Reliability

Security: Per-install random encryption salt replaces hardcoded salt; automatic key migration from v1.0
LLM resilience: Exponential backoff retry (up to 3 attempts) on transient LLM errors (429, 503, timeouts)
Thread safety: Database writes serialized via threading.RLock; safety guard counters protected by locks
Browser management: Context-managed Playwright lifecycle with batch mode for bulk enrichment
IMAP pooling: Persistent IMAP connections with keepalive checks and stale connection recovery
GPU scheduling: Ollama calls serialized via semaphore to prevent GPU contention
Codebase refactor: Extracted db_manager.py (1400+ lines) into migrations.py, seed_agents.py, seed_skills.py
Dev tooling: Added requirements-dev.txt for test/lint dependencies
Tests: 853 → 935 tests (added test_hardening_fixes.py with 82 new tests)

v1.0.0 — Initial Release

Full B2B lead generation pipeline with 20 AI agents
Multi-source lead discovery, deep research, outreach automation
Voice calling, ticket system, 4-tier LLM routing, autonomy controls

License

Distributed under the MIT License. See LICENSE for more information.

Acknowledgments

PySide6 — Desktop UI framework
LiteLLM — Universal LLM API proxy
SQLAlchemy — Python SQL toolkit
Playwright — Browser automation
Twilio — Voice calling infrastructure

Built with Python and a fleet of AI agents.
_{Aura v2.1.0}

Name		Name	Last commit message	Last commit date
Latest commit History 12 Commits
.github/workflows		.github/workflows
assets		assets
controllers		controllers
core		core
database		database
scripts		scripts
tests		tests
ui		ui
utils		utils
.gitignore		.gitignore
DOCUMENTATION.md		DOCUMENTATION.md
LICENSE		LICENSE
README.md		README.md
USER_MANUAL.md		USER_MANUAL.md
aura.spec		aura.spec
cli.py		cli.py
config.py		config.py
main.py		main.py
pyproject.toml		pyproject.toml
requirements-cli.txt		requirements-cli.txt
requirements-dev.txt		requirements-dev.txt
requirements.txt		requirements.txt

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Aura

What is Aura?

The Pipeline

Quick Start

Install the CLI

Install the Desktop App (GUI)

Cross-Platform Notes

First Launch

Features

Lead Discovery & Enrichment

Deep Research

Outreach Automation

AI Agent Fleet

Voice Calling (Last Resort)

Security & Reliability

Autonomy & Control

Integrations

Analytics & Intelligence

CLI Reference

REPL Mode

Command Groups

One-Shot Commands

Architecture

Project Structure

Key Technologies

Configuration

Building from Source

Windows

macOS

Linux

Cross-Platform Build Script

Testing

Documentation

Supported AI Providers

Contributing

Changelog

v2.1.0 — Intelligence & Audit Hardening

v2.0.0 — Enterprise Features + Settings Overhaul

v1.3.0 — Advanced CLI + Cross-Platform

v1.2.0 — Audit Round 2: Deep Hardening

v1.1.0 — Hardening & Reliability

v1.0.0 — Initial Release

License

Acknowledgments

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