Tags: MULTI-AGENT AI SYSTEM · CLIENT RELATIONSHIP INTELLIGENCE · LANGGRAPH + GROQ + FASTAPI
One Line: Replacing the reactive, memory-driven client relationship management cycle at B2B consultancies with an autonomous multi-agent pipeline that ingests real client communications, scores account health continuously, diagnoses relationship risk before it becomes churn, and drafts recovery or expansion outreach — before the client ever sends a cancellation email.
| # | Section | What It Covers |
|---|---|---|
| 01 | Problem Framing | The client health blindspot in B2B consultancies and why current tools fail |
| 02 | Solution Overview | Five-agent pipeline and how each stage works |
| 03 | Multi-Agent AI Architecture | Why LangGraph, the two-model Groq strategy, and the agent separation model were chosen |
| 04 | Agent 0 — Data Ingestion & Identity Resolution | Real email/calendar ingestion, identity mapping, the unmatched queue |
| 05 | Agent 1 — Signal Collector | Event classification — rebuilt from a fiction generator into a real classifier |
| 06 | Agent 2 — Health Scorer | Scoring rubric, damping logic, expansion detection |
| 07 | Agent 3 — Diagnostician | Root cause analysis with evidence-grounding constraints |
| 08 | Agent 4 — Action Drafter | AI-drafted recovery and upsell outreach, human review queue |
| 09 | The Dashboard — Seven Screens | Every screen in detail, design language, admin/demo access split |
| 10 | Technical Architecture — Key Design Decisions | Every architectural decision with rationale and trade-offs |
| 11 | Database Schema — 10 Tables | Full Supabase schema across the intelligence and ingestion layers |
| 12 | The First Live Agent Run — Crossroads Infrastructure | Proof the system works on real classified signals, not fiction |
| 13 | Live Links & Resources | Public URLs and access points |
| 14 | Metrics Framework | Agent performance, pipeline health, business impact |
| 15 | Build Journey & Decision Log | The pivots — from signal generation to real ingestion to production hardening |
| 16 | Product Roadmap | Phased plan from demo to full real-time integration platform |
| 5 Autonomous Agents | 10 Database Tables | 0 Fabricated Signals |
|---|---|---|
| Ingestion → Signal Collector → Health Scorer → Diagnostician → Action Drafter | Full client intelligence data model from raw communication to drafted outreach | Every score and diagnostic is reasoned from real classified events, not LLM-invented data |
| $565K Revenue at Risk Detected | 20+ API Endpoints | Fully Deployed |
| --- | --- | --- |
| Live Apex Advisory Group demo portfolio — 3 of 7 active clients flagged at-risk on first real run | FastAPI backend on Oracle Cloud via Cloudflare Tunnel, JWT-authenticated | Frontend on Vercel, backend on Oracle Cloud, database on Supabase |
03 · Multi-Agent AI Architecture
04 · Agent 0 — Data Ingestion & Identity Resolution
05 · Agent 1 — Signal Collector
09 · The Dashboard — Seven Screens
10 · Technical Architecture — Key Design Decisions