system-prompts-and-models-of-ai-tools/salesflow-saas/MASTER-BLUEPRINT.mdc

---
title: Dealix MASTER-BLUEPRINT
version: Legendary Complete Edition v4.0
status: canonical
---

# Vision

Autonomous Revenue & Operations OS: a **Digital Full-Company Team** for B2B enterprises — Prospecting → Qualification → Proposal → Negotiation → Closing → Post-Sale/Upsell → Support → Marketing → Billing/Finance → Analytics/Forecasting.

> *North star:* not a single chat widget — a **measurable revenue machine** that runs 24/7, self-improves where enabled, and grounds actions in CRM + tenant-safe knowledge.

## Auditable target metrics (directional)

| Axis | Target (vs baseline / program goals) |
|------|--------------------------------------|
| Revenue growth | 3–5× annual lift (customer-specific baselines) |
| Sales efficiency | 70–80% reduction in manual pipeline work |
| Forecast quality | Strong 30-day horizon accuracy (data-dependent) |
| Cycle time | ~40% shorter close cycle where automation applies |
| CAC | ~31% lower acquisition cost via automation + routing |
| Compliance | PDPL-aligned handling; SOC2-ready logging & controls posture |
| Expansion | Multi-region / vertical over 18–36 months |

**Targets:** 3–5× revenue lift, 70–80% manual work reduction, measurable ROI from day one.

## Design principles (non-negotiable)

1. **Value-first** — Every feature ties to a measurable customer or ops outcome.
2. **Compliance-by-design** — Approvals, audit trails, data minimization; not bolt-on.
3. **Self-evolving** — Self-improvement loop + experiments behind flags (see OpenClaw flows).
4. **Complexity hidden, simplicity exposed** — Rich orchestration; simple UX (chat + dashboards).
5. **Measurable everything** — Executive ROI, per-tenant LLM cost where enabled, SLOs.
6. **Zero-trust between tenants** — Strict isolation; sensitive actions behind hooks/approvals.

## Roadmap phases (0–36 months)

| Phase | Window | Focus |
|-------|--------|--------|
| 0 — Foundation | 0–90 days | Production hardening, health checks, pilot, unified GTM assets |
| 1 — MVP revenue | Mo 2–3 | Deeper qualification, proposals, baseline ROI, pilot→paid |
| 2 — Scale | Mo 4–9 | Enterprise patterns, voice GA path, predictive layer, API surface |
| 3 — Dominate | Mo 10–36 | Regions, partnerships, vertical OS variants |

Arabic narrative + detail: `docs/ULTIMATE_EXECUTION_MASTER_AR.md`.

# Core Stack (non-negotiable)

| Layer | Technology |
|-------|------------|
| Planning | **LangGraph** — graphs, subgraphs, checkpointing, time travel |
| Durable runtime | **OpenClaw 2026.4.2** — Durable Task Flow, revision tracking, child tasks, `before_agent_reply`, plugin boundaries |
| Memory | **Mem0** (scoped per agent/deal/customer/tenant) + **Letta** (tiered) + Claude 3-layer self-healing — persisted in flow state |
| LLM | **Claude Opus 4.6** primary; intelligent routing to GPT / Kimi / Copilot-class models |
| Experience UI | **Dealix Next.js** frontend — dashboards, landing, analytics; calls FastAPI (`/api/v1/*`) |
| CRM / Agents | **Salesforce Agentforce 360** — native + A2A + Voice |
| Channels | WhatsApp Cloud, Email (Resend/SendGrid), Stripe, Apollo, Gong, LinkedIn, Slack |
| Governance | Zero-trust AI, SOC2 posture, immutable audit logs, explainability, **HITL** for pricing/closing/contracts |
| Multi-tenant | White-label SaaS, strict tenant isolation, plugin marketplace |

*Onyx and similar external RAG/chat stacks are **out of scope** — not used and must not be added. Product RAG is **in-app** only: PostgreSQL + pgvector, `KnowledgeService`, sector assets, and orchestrator-grounded context.*

# Five Architecture Layers

1. **Experience** — Dealix web app, dashboards, mobile field API  
2. **Orchestration** — LangGraph supervisors, OpenClaw durable flows  
3. **Intelligence** — 40+ agents (swarm + reflection), signal selling, predictive revenue  
4. **Data & Memory** — CRM grounding, Mem0/Letta, audit store  
5. **Integration** — OpenClaw plugins (Salesforce, WhatsApp, Stripe, Voice, Contracts)

# Self-Improvement Loop v2.0 (6 phases)

Observation → Analysis → Hypothesis → Shadow experiments → Canary + revision tracking → Meta-learning.  
Feeds: app analytics, LangSmith traces (when enabled), OpenClaw outcomes — improves prompts, tools, memory schemas, agent behavior.

# Salesforce (grounding)

- CRM data via Agentforce / REST APIs; permission-aware access in production.  
- Qualification, Proposal, Support, and Analytics agents consume grounded CRM context.

# Repository mapping

- `openclaw/openclaw-config.yaml` — durable flows + hooks + plugins  
- `backend/app/openclaw/` — runtime helpers, hooks, plugins  
- `backend/app/api/v1/autonomous_foundation.py` — autonomous flows, go-live gate, connectivity tests  
- `backend/app/services/knowledge_service.py` — in-app RAG (pgvector / sector assets)  
- `backend/app/ai/orchestrator.py` — lead/message routing + knowledge context  
- `backend/app/agents/` — LangGraph / master agent wiring (evolves per release)  
- `docs/ULTIMATE_EXECUTION_MASTER_AR.md` — full Arabic execution narrative aligned to this blueprint  
- `frontend/` — Dealix UI (Next.js)

# Agent / crew map (conceptual — implementation in `backend/app/agents`, flows, services)

Prospecting → Qualification → Proposal → Negotiation → Closing → Post-sale/Support. Each stage may map to supervisors + tool plugins (Salesforce, WhatsApp, Stripe, voice, contracts) within OpenClaw boundaries — **no external RAG SaaS as the system of record**; use native knowledge + CRM grounding.

*This file is the single source of truth for architecture intent; implementation evolves in code beside it.*