mancitrus/system-prompts-and-models-of-ai-tools
1
0
Fork 0
mirror of https://github.com/x1xhlol/system-prompts-and-models-of-ai-tools.git synced 2026-06-18 07:19:35 +00:00
Code Issues Actions Packages Projects Releases Wiki Activity
711dca7acf
system-prompts-and-models-o.../salesflow-saas/memory/architecture/system-overview.md
Claude a329957a3b
feat: Add AI engine, PDPL compliance, sequences, CPQ, and governance layers 
Phase 1-6 implementation for Dealix AI Revenue OS:

- AI Arabic Engine: NLP (arabic_nlp.py), lead scoring (lead_scoring.py)
- PDPL Compliance: consent manager, data rights handler, consent model
- Sequence Engine: multi-channel sequences with WhatsApp/Email/SMS
- CPQ System: quote engine, AI proposal generator
- Security Gate: pre-release checks, PDPL message validation
- Tool Verification: agent action audit trail
- Project Operating Files: AGENTS.md, CLAUDE.md
- Project Memory: architecture, ADRs, provider routing, PDPL checklist
- Design System: IBM Plex Sans Arabic tokens, RTL-safe components
- Sequence/Consent models for database

https://claude.ai/code/session_01LsnvBa7HwF5hs99VZbgLGj
2026-04-11 07:40:39 +00:00

3.4 KiB
Raw Blame History

Dealix System Architecture Overview

Type: architecture Date: 2026-04-11 Status: active Confidence: high

Summary

Dealix is a multi-tenant AI-powered CRM SaaS targeting Saudi SMBs. Architecture follows a microservices-ready monolith pattern.

Components

┌─────────────────────────────────────────────────────────┐
│                    Nginx (Reverse Proxy)                  │
├──────────────────────┬──────────────────────────────────┤
│   Next.js Frontend   │         FastAPI Backend           │
│   (Port 3000)        │         (Port 8000)               │
│   - Dashboard        │   ┌─────────────────────────┐    │
│   - Landing          │   │   API Layer (v1)         │    │
│   - Auth             │   │   - Auth, Leads, Deals   │    │
│   - Pipeline         │   │   - Inbox, Sequences     │    │
│                      │   │   - Compliance, Proposals │    │
│                      │   ├─────────────────────────┤    │
│                      │   │   Services Layer          │    │
│                      │   │   - AI Engine (Arabic)    │    │
│                      │   │   - PDPL Compliance       │    │
│                      │   │   - Sequence Engine       │    │
│                      │   │   - CPQ System            │    │
│                      │   │   - Agent Orchestrator    │    │
│                      │   ├─────────────────────────┤    │
│                      │   │   Integration Layer       │    │
│                      │   │   - WhatsApp, Email, SMS  │    │
│                      │   │   - Stripe, ZATCA         │    │
├──────────────────────┴───┴─────────────────────────┤    │
│        Celery Workers (4)    │    Celery Beat        │    │
├──────────────────────────────┴──────────────────────┤    │
│   PostgreSQL 16     │     Redis 7                    │    │
└─────────────────────┴───────────────────────────────┘

Key Design Decisions

  • Multi-tenant isolation: tenant_id on every table, enforced at query level
  • Arabic-first: RTL layout, Arabic NLP, Saudi dialect support
  • WhatsApp-first: Primary communication channel (85% Saudi penetration)
  • PDPL-native: Consent checked before every outbound message
  • LLM fallback chain: Groq → OpenAI for cost optimization
  • Async everything: asyncpg, async SQLAlchemy, async HTTP clients

Related Topics