system-prompts-and-models-of-ai-tools/salesflow-saas/CLAUDE.md

CLAUDE.md — Dealix Project Context for AI Agents

Quick Context

Dealix is an AI-powered CRM built for the Saudi market. It combines Salesforce-grade AI with WhatsApp-first communication, PDPL compliance, and Arabic-first UX.

Key Directories

• backend/app/api/v1/ — API routes (FastAPI)
• backend/app/models/ — SQLAlchemy models
• backend/app/services/ — Business logic layer
• backend/app/services/ai/ — AI engine (Arabic NLP, scoring, forecasting)
• backend/app/services/pdpl/ — PDPL compliance engine
• backend/app/services/cpq/ — Configure, Price, Quote
• backend/app/services/agents/ — Multi-agent orchestration
• backend/app/services/llm/ — LLM provider abstraction
• backend/app/workers/ — Celery async tasks
• backend/app/integrations/ — WhatsApp, Email, SMS adapters
• frontend/src/app/ — Next.js pages
• seeds/ — Industry templates (JSON)
• memory/ — Project knowledge base

Database

• PostgreSQL 16 with async driver (asyncpg)
• Multi-tenant: every table has tenant_id
• Alembic for migrations
• Money fields use Numeric type (never Float)

AI Architecture

• Provider abstraction: Groq → OpenAI fallback
• Model router: task-specific model selection
• Arabic NLP: intent, sentiment, entity extraction
• Lead scoring: 0-100 composite score
• Conversation intelligence: Arabic dialogue analysis
• Sales agent: autonomous WhatsApp qualification bot

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 in main.py
• Add new model: create in models/, add to models/__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.py for: 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-search in 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