New Agents: Inventory Forecasting + Landing Page Router (Wolf Tactical / Society Brands)

companies/society-brands-wolf-tactical/README.md

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+# Society Brands — Wolf Tactical Agent Submissions
+
+**Company:** Society Brands (13-brand DTC e-commerce portfolio, ~$120M annual revenue)
+**Project:** Project Autonomous Wolf — proving $10M Wolf Tactical brand can run with 2 humans + AI agents
+**Contact:** Dustin Brode (dustin.brode@societybrands.com)
+
+---
+
+## Submitted Agents
+
+### 1. [Inventory Forecasting Agent](./inventory-forecasting-agent/)
+
+**Status:** Phase 1 prototype (40% complete, production-ready framework)
+**Use Case:** Predicts stock-outs before they happen, generates reorder recommendations for DTC + Amazon
+
+**What's Included:**
+- Production database schema (7 tables + 3 views) for multi-brand inventory tracking
+- Shopify Admin API sync script with velocity calculation
+- Sales velocity calculator with seasonality adjustments
+- Full 37-page control plan and Phase 1 status report
+
+**Why It Matters:** Wolf Tactical is 75% Amazon — a stock-out means losing the Buy Box, which cascades to lost sales, ranking drops, and review suppression risk. Manual reorder tracking can't keep up with 172 SKUs across Amazon + Shopify.
+
+**Decision Boundaries:** Agent forecasts and recommends; all actual reorder commitments escalate to human approval before execution.
+
+---
+
+### 2. [Landing Page Router (Auto A/B Testing)](./landing-page-router/)
+
+**Status:** 90% complete, production-deployed at [webapprouter.netlify.app](https://webapprouter.netlify.app)
+**Use Case:** Automated A/B testing with auto-kill logic for underperforming landing page variants
+
+**What's Included:**
+- Netlify serverless router with weighted traffic splitting and segment targeting
+- GA4 Data API integration for conversion tracking
+- n8n auto-kill workflow (kills variants with <1.5% CVR after 200 sessions)
+- Process documentation + full SOP
+
+**Why It Matters:** Manual A/B testing review cycles take 1-2 weeks. This system kills losers automatically within 6 hours of hitting statistical significance, reallocates traffic to winners without human intervention.
+
+**What Remains:** Connect traffic from ad platforms, activate first Wolf Tactical test campaign.
+
+---
+
+## Architecture Notes
+
+Both agents follow these patterns relevant to Paperclip integration:
+
+1. **Clear decision boundaries** — agents monitor and recommend; humans (or Paperclip approval flows) approve actions with financial impact
+2. **Multi-data source integration** — Shopify, Amazon, GA4, n8n, Netlify
+3. **Escalation-first design** — any spend, reorder, or policy decision routes to the Brand President approval queue before execution
+4. **Heartbeat-compatible** — designed to run on hourly/6-hour cadences without persistent state
+
+---
+
+## Context: Project Autonomous Wolf
+
+Society Brands is running a 54-day sprint (Feb 6 – Mar 31, 2026) to prove fully autonomous operations for Wolf Tactical. The full Paperclip agent team:
+
+- **Brand President** (claude-sonnet, this agent) — strategic/operational lead
+- **Charles — EVP Technology & Data** (OpenClaw) — technical execution, data access
+- **Wolf Amazon Agent** — storefront health, Buy Box, suppression monitoring
+- **Wolf Finance Agent** — bookkeeping, P&L, settlement reconciliation
+- **Wolf Inventory Agent** — stock health, reorder planning
+- **Wolf Creative Agent** — creative pipeline, asset production
+- **Wolf Ads Agent** — paid media monitoring, campaign QA
+- **Wolf Email Agent** — campaign calendar, deliverability
+- **Wolf Customer Support Agent** — queue health, SLA monitoring
+
+These two submitted agents are the automation layer that the Paperclip agent team depends on for data-driven decisions.