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CLAUDE.md — Dealix Project Context for AI Agents
Quick Context
Dealix is a Sovereign Enterprise Growth OS for GCC Companies. It manages Revenue, Partnerships, Corporate Development/M&A, Expansion, PMI, and Trust/Governance — with AI agents, durable workflows, and policy-enforced execution.
Operating Constitution: See MASTER_OPERATING_PROMPT.md for the canonical reference.
Key Directories
backend/app/api/v1/— API routes (FastAPI)backend/app/models/— SQLAlchemy modelsbackend/app/services/— Business logic layerbackend/app/services/ai/— AI engine (Arabic NLP, scoring, forecasting)backend/app/services/pdpl/— PDPL compliance enginebackend/app/services/cpq/— Configure, Price, Quotebackend/app/services/agents/— Multi-agent orchestrationbackend/app/services/llm/— LLM provider abstractionbackend/app/workers/— Celery async tasksbackend/app/integrations/— WhatsApp, Email, SMS adaptersfrontend/src/app/— Next.js pagesseeds/— Industry templates (JSON)memory/— Project knowledge basedocs/governance/— Governance framework (execution-fabric, trust-fabric, compliance, radar)docs/adr/— Architecture Decision Recordsscripts/— Architecture brief and toolingMASTER_OPERATING_PROMPT.md— Operating constitution (five planes, six tracks, policy classes)
Database
- PostgreSQL 16 with async driver (asyncpg)
- Multi-tenant: every table has
tenant_id - Alembic for migrations
- Money fields use
Numerictype (never Float)
AI Architecture — Autonomous Revenue OS (Level 5)
- Provider abstraction: Groq → OpenAI fallback
- Model router: task-specific model selection
- Arabic NLP: intent, sentiment, entity extraction
- Lead scoring: 0-100 composite score (4 axes)
- Multi-agent system: 20 specialized AI agents
Agent System (services/agents/)
router.py— Agent registry with priority, parallel/sequential execution, retryexecutor.py— LLM calls + output parsing + escalation + action dispatchautonomous_pipeline.py— 11-stage state machine (NEW → WON/LOST)action_dispatcher.py— Routes 13 action types to external servicesmanus_orchestrator.py— Multi-agent orchestration layer
AI Agent Prompts (ai-agents/prompts/) — 20 files
| Category | Agents |
|---|---|
| Sales Core | closer, lead_qualification, outreach_writer, meeting_booking |
| Communication | arabic_whatsapp, english_conversation, voice_call |
| Intelligence | objection_handler, proposal_drafter, sector_strategist, ai_rehearsal |
| Analytics | revenue_attribution, management_summary, knowledge_retrieval |
| Compliance | compliance_reviewer, fraud_reviewer, qa_reviewer |
| Affiliates | affiliate_evaluator, onboarding_coach, guarantee_reviewer |
Pipeline Stages
NEW → QUALIFYING → QUALIFIED → OUTREACH → MEETING_SCHEDULED → MEETING_PREP → NEGOTIATION → CLOSING → WON/LOST/NURTURING
Key API Endpoints
POST /pipeline/process-lead— Full autonomous pipelinePOST /pipeline/advance-stage— Manual stage advanceGET /agent-health/status— System health checkPOST /agent-health/self-improve— Trigger optimization cycle
PDPL Compliance (Critical)
- Check consent before ANY outbound message
- Track consent purpose, channel, timestamp
- Support data subject rights (access, correct, delete)
- Audit trail for all consent changes
- Auto-expire consent after 12 months
- Penalty: up to SAR 5 million per violation
Testing
pytest -v # All tests
pytest tests/test_ai/ -v # AI engine tests
pytest tests/test_pdpl/ -v # PDPL compliance tests
pytest tests/test_api/ -v # API endpoint tests
Common Tasks
- Add new API endpoint: create route in
api/v1/, register inmain.py - Add new model: create in
models/, add tomodels/__init__.py, create migration - Add new AI feature: create in
services/ai/, wire to relevant API/worker - Add industry template: create JSON in
seeds/, match existing schema
gstack Planning Discipline
Before writing code, classify your task:
| Tier | When | What to do |
|---|---|---|
| SIMPLE | 1 file, obvious change | Just do it |
| MEDIUM | Multi-file, needs thought | Read files → 5-line plan → resolve ambiguity → self-review → report |
| HEAVY | Complex, needs specific skill | Load skill → execute workflow → verify → report |
| FULL | End-to-end feature/release | Plan → review → implement → test → ship → report |
| PLAN | Research/architecture only | Plan only, save to memory/, no implementation |
RULE: Append to this file, never replace existing instructions.
Hermes Profiles
| Profile | Mission | Scope |
|---|---|---|
growth |
Customer acquisition | leads, messaging, analytics, content |
sales |
Deal closing | deals, proposals, sequences, WhatsApp |
security |
Platform protection | compliance, audit, Shannon scans |
ops |
Deployment & reliability | workers, monitoring, releases |
knowledge |
Wiki & memory management | brain, wiki, indexes |
founder |
Strategic decisions | everything (highest permissions) |
arabic-ops |
Arabic content & dialect | summarization, dialect detection, RTL |
Arabic Operations
- Use
arabic_ops.pyfor: call notes compression, market research digests, executive briefs - Always detect dialect before processing (saudi/gulf/msa)
- Check for Arabizi and suggest Arabic conversion
- Check code-switching (Arabic+English mixed) for readability
claude-mem (Persistent Memory)
Installed and active. Automatically captures every session's work and injects context into new sessions.
- Worker:
npx claude-mem start(port 37777) - Web UI: http://localhost:37777
- Search: Use
/mem-searchin Claude Code - Data:
~/.claude-mem/claude-mem.db(SQLite + Chroma vectors) - Privacy: Wrap sensitive content in
<private>...</private>tags - Token savings: ~95% reduction via 3-layer progressive retrieval
- Auto-captures: tool executions, session summaries, decisions, bugs, patterns
Governance Framework (Tier-1)
- Five Planes: Decision, Execution, Trust, Data, Operating — see
docs/ai-operating-model.md - Six Tracks: Revenue, Intelligence, Compliance, Expansion, Operations, Trust — see
docs/dealix-six-tracks.md - Policy Classes: A (auto), B (approval), C (forbidden) — enforced by
openclaw/policy.py - Contradiction Engine: Detect/track system conflicts —
services/contradiction_engine.py - Evidence Packs: Tamper-evident audit proof —
services/evidence_pack_service.py - Saudi Compliance Matrix: Live PDPL/ZATCA/SDAIA/NCA controls —
services/saudi_compliance_matrix.py - Architecture Preflight:
python scripts/architecture_brief.py(run from repo root)