Targeting & Acquisition OS (16 modules) — نظام الاستهداف الذكي - account_finder: account-first targeting; 12 buying signals; deterministic 10-25 accounts per (sector, city) - buyer_role_mapper: 14 buyer roles + sector-specific buying-committee maps + role-based Arabic angles - contact_source_policy: 12 sources (crm_customer→opt_out) with risk_score, channels-allowed, retention guidance, lawful_basis - contactability_matrix: 5 action modes (suggest_only/draft_only/approval_required/approved_execute/blocked); opt-out always blocked - linkedin_strategy: Lead Forms + Ads + manual ONLY; linkedin_do_not_do() locks scrape/auto-DM/auto-connect/extensions - email_strategy: drafts + unsubscribe footer + domain-pacing (fresh/warmed/trusted/damaged) + spam-trigger risk - whatsapp_strategy: opt-in only; rejects cold + risky phrases; opt-in template requires explicit purpose+company+unsubscribe - social_strategy: official APIs only; listening + drafts; no auto-publish - outreach_scheduler: day-by-day plans + daily limits + opt-out enforcement - reputation_guard: bounce/complaint/opt-out thresholds → healthy/watch/pause + recovery actions per channel - daily_autopilot: Arabic brief + 7 today actions + EOD report - acquisition_scorecard: pipeline + meetings + risks + productivity_score - self_growth_mode: 5 ICP focuses for Dealix; daily brief + monthly targets - free_diagnostic: Free Growth Diagnostic (3 ops + msg + risk + plan) → paid pilot recommendation - contract_drafts: Pilot/DPA/Referral/Agency/SOW outlines (legal_review_required, PDPL-aware) - service_offers: 7 targeting-tier offers + recommend by customer-type Service Tower (8 modules) — برج الخدمات الذاتية (12 productized services) - service_catalog: 12 services with target_customer/outcome/inputs/workflow/deliverables/pricing/risk/proof/upgrade - service_wizard: deterministic recommend (agency→partner; list→list_intelligence; founder→self_growth; CEO→exec_brief; budget≥2999→growth_os; default→first_10) - mission_templates: workflow steps with approval gates + linked growth missions - pricing_engine: SAR quotes scaled by company_size×urgency×channels_count + setup_fee + monthly_offer - deliverables: client report outline + proof pack template + operator checklist (no live actions) - service_scorecard: 0..100 score from drafts/replies/meetings/pipeline/CSAT - whatsapp_ceo_control: daily brief, approval cards (≤3 buttons), risk alerts, EOD reports - upgrade_paths: deterministic next-service recommendation + Arabic upsell messages Service Excellence OS (8 modules) — مصنع الخدمات الممتازة - feature_matrix: 12 must-have features per service + advanced/premium/future tiers - service_scoring: 10-dimension excellence score (clarity, speed_to_value, automation, compliance, proof, upsell, uniqueness, scalability, ops_daily, proof_data) → launch_ready/beta_only/needs_work - quality_review: 4 gates (proof / approval / pricing / channels) + status verdict; review_service_before_launch and review/all - competitor_gap: 7 competitor categories (CRM, WhatsApp tools, email assistants, LinkedIn tools, agencies, revenue intelligence, generic AI) + Dealix advantages + do-not-copy - proof_metrics: required metrics + ROI estimate (pipeline_x + closed_won_x) + Arabic summary - research_lab: monthly brief + feature hypotheses + top-3 experiments + monthly review - service_improvement_backlog: feedback→backlog conversion + impact/effort prioritization + weekly improvements - launch_package: landing outline + sales script + 12-min demo script + 5-day onboarding checklist Routers (3 new) — 62 endpoints - /api/v1/targeting/* — 20 endpoints (accounts, buying-committee, contacts, uploaded-list, outreach, daily-autopilot, self-growth, reputation, linkedin, drafts, free-diagnostic, services, contracts) - /api/v1/services/* — 20 endpoints (catalog, recommend, intake, start, workflow, deliverables, proof-pack, quote, setup-fee, monthly-offer, scorecard, upgrade-path, ceo daily-brief/approval-card/risk-alert/EOD) - /api/v1/service-excellence/* — 22 endpoints (feature-matrix, score, quality-review, review/all, proof-metrics, roi-estimate, gap-analysis, research-brief, hypotheses, experiments, monthly-review, backlog, weekly-improvements, launch-package, landing/sales/demo/onboarding) Tests (3 new files, 105 tests) - test_targeting_os: 47 tests (Arabic accounts, buying committees, opt-out blocked, cold WA blocked, LinkedIn no-scraping, email unsubscribe, WA risk, outreach plan, reputation guard, self-growth, contracts, scorecard) - test_service_tower: 38 tests (12+ services, all have pricing/proof/deliverables/approval, wizard recommendations, workflow includes approval, quote scales, CEO cards ≤3 buttons, no live send) - test_service_excellence: 33 tests (feature matrix, score returns status, ALL services pass quality gates, ROI x-multiples, 7 competitor categories, hypotheses+experiments, backlog conversion, launch package complete, demo=12min) Docs (3 new + 1 updated) - TARGETING_ACQUISITION_OS.md (Arabic) - SERVICE_TOWER_STRATEGY.md (Arabic) - SERVICE_EXCELLENCE_OS.md (Arabic) - DEALIX_100_PERCENT_LAUNCH_PLAN.md — added §36 Targeting OS + §37 Service Tower + §38 Service Excellence + §39 Landing Pages Landing pages (4 new, RTL Arabic) - services.html — 3 doors + 12 productized services - free-diagnostic.html — free growth diagnostic - first-10-opportunities.html — kill feature - agency-partner.html — agency partner program Test results - 105/105 new tests pass - Full suite: 768 passed, 2 skipped - 0 existing tests broken Safety + integration with previous layers - Targeting OS uses contactability_matrix → ALL contacts gated before any send - Service Tower's workflow includes approval gate; ALL services live_send_allowed=False - Service Excellence quality_review BLOCKS launch on missing proof/approval/pricing/unsafe channels - linkedin_do_not_do() encodes 8 explicit prohibitions (scraping/auto-DM/auto-connect/extensions) - whatsapp_do_not_do() blocks cold sends + group scraping - Contracts always: legal_review_required=True, not_legal_advice=True, PDPL sections present - Self-Growth Mode lets Dealix target its OWN ICP using the same approval-first pipeline Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
||
|---|---|---|
| .. | ||
| .cursor/rules | ||
| .github | ||
| api | ||
| auto_client_acquisition | ||
| autonomous_growth | ||
| core | ||
| dashboard | ||
| db | ||
| dealix | ||
| docs | ||
| evals | ||
| integrations | ||
| landing | ||
| scripts | ||
| supabase/migrations | ||
| tests | ||
| .dockerignore | ||
| .editorconfig | ||
| .env.example | ||
| .env.staging.example | ||
| .gitignore | ||
| .gitleaks.toml | ||
| .pre-commit-config.yaml | ||
| .secrets.baseline | ||
| CHANGELOG.md | ||
| cli.py | ||
| CODE_OF_CONDUCT.md | ||
| CONTRIBUTING.md | ||
| DEALIX_COMPANY_OPERATIONAL_STATE.md | ||
| DEPLOYMENT.md | ||
| docker-compose.yml | ||
| Dockerfile | ||
| LICENSE | ||
| Makefile | ||
| Procfile | ||
| pyproject.toml | ||
| QUICK_START.md | ||
| railway.json | ||
| railway.toml | ||
| README.ar.md | ||
| README.md | ||
| requirements-dev.txt | ||
| requirements.txt | ||
| SECURITY.md | ||
| v3_app.py | ||
🏢 Dealix — AI Company Saudi
Sovereign, policy-governed Growth & Execution OS for Saudi enterprises
نظام نمو وتنفيذ سيادي محكوم بالسياسات، للشركات السعودية
العربية · English
🚀 Deploy Now · 📦 .env Template · 🎯 Landing · 🗺️ API Map · 🏢 Day 1 Plan
🎯 What's in this repo
Backend — FastAPI + SQLAlchemy 2.0 async + Postgres. 13 routers / 102 endpoints. See API_MAP.md.
Lead Machine — Provider adapter chains for Search / Maps / Crawler / Tech / EmailIntel that fall back gracefully when env keys are missing. See PROVIDER_ADAPTERS.md.
Data Lake + Lead Graph — 7-table compliant ingestion: raw_lead_imports → raw_lead_rows → accounts → contacts → signals → lead_scores → data_suppression_list. PDPL-aware (allowed_use, consent_status, opt_out, risk_level mandatory per row). See DATA_LAKE_PLAYBOOK.md.
Frontend — Static landing on GitHub Pages + interactive dashboard with live Saudi Lead Engine demo. See landing/.
Day-1 Operating Kit — 287 outreach-ready Saudi B2B accounts pre-built across 7 segments (real-estate / construction / hospitality / events / food / logistics / SaaS / agency). Pricing ladder + Pilot offer + Partner model + Channel templates. See docs/business/.
⚡ Quick Deploy
Any Docker-capable platform works. See DEPLOYMENT.md for Railway, Render, Fly.io, Heroku, DigitalOcean, AWS, self-hosted.
# Local
docker build -t dealix .
cp .env.example .env # edit with real values
docker run -p 8000:8000 --env-file .env dealix
curl localhost:8000/health
Public endpoints (no auth): /health, /api/v1/public/demo-request, /api/v1/pricing/plans, /api/v1/checkout, /api/v1/webhooks/moyasar
🌟 One-line definition
Dealix is a sovereign, policy-governed Growth & Execution OS for Saudi enterprises. It combines agentic intelligence, deterministic execution, approval controls, and executive observability to drive revenue, partnerships, expansion, and strategic operations with enterprise-grade trust.
It is not a CRM, not a chatbot, not a sales automation tool.
🧭 The Prime Operating Rule
AI explores, analyzes, and recommends. Deterministic workflows execute. Humans approve critical moves.
No agent makes an external commitment on its own. No critical output leaves the system without being structured, evidence-backed, policy-evaluated, and (where required) human-approved.
🧱 The six OS tracks
- Revenue OS — lead to close, pipeline, forecasting
- Partnership OS — partner discovery, joint pursuits, co-sell
- Corporate Development / M&A OS — sourcing, diligence, integration
- Expansion OS — new-market entry, localization
- PMI / Strategic PMO OS — post-merger integration, cross-BU initiatives
- Trust, Policy & Executive Governance OS — controls, approvals, risk, audit
🏗️ Five mandatory planes
Every feature lives in exactly one plane. Crossing planes happens via contracts, never via shared memory or direct calls.
| Plane | Responsibility | Module |
|---|---|---|
| Decision | Agents: reasoning, synthesis, recommendation, evidence assembly | auto_client_acquisition/, autonomous_growth/, core/agents/ |
| Execution | Durable workflows, retries, compensation, external commitments | auto_client_acquisition/pipeline.py, dealix/execution/ |
| Trust | Policy, approval, audit, tool verification, evidence packs | dealix/trust/ |
| Data | Operational source of truth, semantic metrics, lineage | db/, integrations/ |
| Operating | Repo governance, CI/CD, releases, SDLC security | .github/, Dockerfile, Makefile |
🛡️ What makes this Tier-1
1. Structured outputs with classifications
Every critical agent output is a validated DecisionOutput (Pydantic + JSON Schema) carrying:
- Approval class (A0–A3): who must approve
- Reversibility class (R0–R3): how hard to undo
- Sensitivity class (S0–S3): data/impact risk
2. Trust Plane as a non-bypassable overlay
Every NextAction runs through a PolicyEvaluator that returns ALLOW / DENY / ESCALATE. Escalations create ApprovalRequests with TTL + multi-approver support. Every step is audited.
3. Never-auto-execute list
Hardcoded in dealix/classifications/NEVER_AUTO_EXECUTE: pricing commits, contract changes, NDAs, payment terms, regulator comms, sensitive data exports — these cannot bypass human approval, regardless of other signals.
4. Evidence packs on high-stakes decisions
A2+/R3/S3 decisions cannot be constructed without evidence — Pydantic validator enforces it. Every pack ships with sources, tool calls (intended vs actual), prompts used, model versions, and a bilingual AR/EN board-grade memo.
5. No-overclaim register
Every public product claim is tracked in dealix/registers/no_overclaim.yaml with status (Production / Partial / Pilot / Planned) and evidence paths.
6. Saudi-native from day one
Not localization — Gulf business register Arabic, SAR pricing tiers, Riyadh timezone awareness, PDPL lawful-basis enforcement via policy rules, NCA ECC/DCC/CCC mapping in dealix/registers/compliance_saudi.yaml.
✨ Core technical features
- 🧠 Multi-LLM routing with fallback — Claude, Gemini, Groq, DeepSeek, GLM, OpenAI. Task → best provider → auto-fallback on failure. Per-provider usage tracking.
- 🤖 15+ production agents — typed I/O, structured logging, graceful degradation, 63 tests.
- 🌍 First-class bilingual AR/EN — detection, routing (Arabic → GLM), content generation, sales scripts, docs.
- 🔒 Security-first —
.env-only config,SecretStreverywhere, gitleaks + detect-secrets + trufflehog + bandit in pre-commit AND CI, webhook HMAC verification, non-root Docker, ToS-safe LinkedIn. - 🐳 Cloud-ready — multi-stage Dockerfile, docker-compose stack (Postgres + Redis + Mongo), GitHub Actions CI/CD, GHCR image push on release tags.
- 📊 Observable — structlog JSON logs in prod, request IDs, per-provider LLM usage metrics, optional Langfuse integration.
🏗️ Architecture
graph TB
subgraph Clients
W[Website Forms]
WA[WhatsApp Business]
E[Email]
end
subgraph Gateway["FastAPI Gateway"]
R[6 routers + middleware]
end
subgraph Decision["Decision Plane — agents"]
I[Intake] --> P[Pain Extract]
P --> IC[ICP Match]
IC --> Q[Qualification]
end
subgraph Trust["Trust Plane — NON-BYPASSABLE"]
POL[Policy Evaluator]
APR[Approval Center]
AUD[Audit Sink]
TV[Tool Verification Ledger]
end
subgraph Execution["Execution Plane — deterministic"]
CRM[HubSpot sync]
BK[Booking]
PS[Proposal send]
end
subgraph LLM["LLM Router — fallback"]
CL[Claude]
GM[Gemini]
GQ[Groq]
DS[DeepSeek]
GL[GLM]
end
Clients --> Gateway
Gateway --> Decision
Decision --> Trust
Trust -->|ALLOW| Execution
Trust -->|ESCALATE| HUMAN[Human approver]
HUMAN --> Execution
Decision --> LLM
Trust --> AUD
Full blueprint: docs/blueprint/master-architecture.md.
🚀 Quick start
git clone https://github.com/YOUR-ORG/ai-company-saudi.git
cd ai-company-saudi
make setup
# edit .env, then:
make run
# → http://localhost:8000/docs
Full stack (app + Postgres + Redis + Mongo):
make docker-up
Try the governed pipeline
curl -X POST http://localhost:8000/api/v1/leads \
-H "Content-Type: application/json" \
-d '{
"company": "شركة التقنية المتقدمة",
"name": "أحمد محمد",
"email": "ahmed@example.sa",
"phone": "+966501234567",
"sector": "technology",
"region": "Saudi Arabia",
"budget": 50000,
"message": "نحتاج نظام AI لإدارة المبيعات"
}'
Use the GovernedPipeline directly (shows the governance layer)
import asyncio
from dealix.execution import GovernedPipeline
async def main():
gp = GovernedPipeline()
result = await gp.run(payload={
"company": "...",
"name": "...",
"message": "..."
})
print(f"Decisions: {len(result.decisions)}")
print(f"Policy results: {len(result.policy_results)}")
print(f"Approval requests: {len(result.approval_requests)}")
print(f"Audit trail: {len(result.audit_trail)} entries")
asyncio.run(main())
📚 The twelve Master Documents
All under dealix/masters/ and dealix/registers/:
- Master Architecture Blueprint — canonical source of truth
- AI Operating Constitution — binding rules
- Trust Fabric Specification
- Execution Fabric Specification
- Repo Operating Pack
- 90-Day Execution Matrix
- Saudi Compliance Register — PDPL + NCA + AI governance
- Technology Radar
- Incident & Rollback Runbook
- Release Readiness Checklist
- No-Overclaim Register — every public claim tracked
- Evidence Pack Specification
🧪 Testing
make test # 63 tests, all passing
Tests include: intake, ICP matcher, pain extractor, model router, API endpoints, full Phase 8 pipeline, Dealix contracts (with high-stakes validation), Trust Plane (policy + approval + audit + tool verification), Governed pipeline end-to-end.
🧰 Tech stack
| Layer | Choice | Status |
|---|---|---|
| Language | Python 3.11 / 3.12 | ADOPT |
| Framework | FastAPI 0.115 + Uvicorn | ADOPT |
| Validation | Pydantic v2 + pydantic-settings | ADOPT |
| Contracts | JSON Schema + CloudEvents 1.0 | ADOPT |
| DB | PostgreSQL 16 + pgvector | ADOPT |
| LLM | Claude, Gemini, Groq, DeepSeek, GLM, OpenAI fallback | ADOPT |
| Execution | In-process → LangGraph → Temporal spike | TRIAL→ADOPT |
| Trust — Policy | In-process → OPA/Rego | TRIAL |
| Trust — AuthZ | In-process → OpenFGA | TRIAL |
| Trust — Identity | local → Keycloak | TRIAL |
| Trust — Secrets | .env + SecretStr → Vault |
TRIAL |
| Observability | structlog → OpenTelemetry | TRIAL |
| CI/CD | GitHub Actions + rulesets + OIDC | ADOPT |
Full radar: dealix/registers/technology_radar.yaml.
📊 Phase 8 — Acquisition agents
All 9 agents + pipeline. Every output lifts to a DecisionOutput via dealix.contracts.builders.
| Agent | Classification | Role |
|---|---|---|
| Intake | A0/R0/S2 | Multi-source lead capture, normalization, dedup |
| ICP Matcher | A0/R0/S1 | 5-dim weighted Fit scoring with tier A/B/C/D |
| Pain Extractor | A0/R0/S1 | Hybrid keyword + LLM pain extraction (AR+EN) |
| Qualification | A0/R0/S1 | BANT questions, status advancement |
| Booking | A1/R1/S2 | Calendly → Google Calendar → manual (requires approval) |
| CRM | A0→A1/R1/S2 | HubSpot contact upsert (A0) + deal create (A1) |
| Proposal draft | A0/R0/S2 | Claude-authored, region-aware pricing |
| Proposal send | A2/R2/S2 | Gated — requires manager + legal approval |
| Outreach | A1/R2/S2 | Bilingual cold openers — gated |
| Follow-up | A1/R2/S2 | Cadence-based — gated |
📈 Phase 9 — Growth agents
| Agent | Role |
|---|---|
| Sector Intel | 12 Saudi sectors with curated market size, growth, AI readiness |
| Content Creator | Bilingual articles, LinkedIn, case studies, newsletters |
| Distribution | Multi-channel scheduling (Riyadh timezone) |
| Enrichment | Domain + LLM-based lead enrichment |
| Competitor Monitor | Positioning, pricing hints, counter-moves |
| Market Research | Gemini-powered research with bullet findings |
🔒 Security
.env-only config viapydantic-settings;SecretStron every sensitive value- Pre-commit:
gitleaks,detect-secrets,bandit,hadolint - CI: re-runs the above +
trufflehogon every push and PR - Webhook HMAC verification (WhatsApp)
- Non-root Docker container with healthcheck
- LinkedIn integration disabled by default (ToS compliance)
- See SECURITY.md for reporting vulnerabilities
🇸🇦 Saudi compliance
Designed from inception for:
- PDPL — lawful-basis register, retention schedule, breach response, DPO assessment, cross-border transfer posture
- NCA ECC 2-2024 — Essential Cybersecurity Controls
- NCA DCC-1:2022 — Data Cybersecurity Controls
- NCA CCC 2:2024 — Cloud Cybersecurity Controls
- NIST AI RMF 1.0 + OWASP Top 10 for LLM Applications
Full register: dealix/registers/compliance_saudi.yaml.
🤝 Contributing
See CONTRIBUTING.md and Repo Operating Pack. By participating you agree to the Code of Conduct.
📜 License
MIT — see LICENSE.