Know exactly where your AI infrastructure stands — in 90 seconds.
AI Stack Doctor is a free, open-source AI infrastructure audit tool that gives any company a complete health check of their AI stack — with scores, peer benchmarks, ROI estimates, compliance flags, and a prioritized action plan. Built for consultants, executives, and technical teams. No technical background required.
From the State of Martech 2026 (Brinker & Riemersma, n=208 marketing & martech leaders):
| Stat | Finding |
|---|---|
| 88 / 130 | Marketing leaders NOT using AI to manage their own stack — highest gap of any AI use case surveyed |
| Only 8% | Of organizations report full confidence in their AI governance readiness |
| 73% | Have a formal GenAI policy — but a policy is not a finish line |
| 7.1% | Growth in Governance, Compliance & Privacy tools — one of only 11 subcategories growing |
| −37 net | Content Marketing tools lost — first wave of AI content tools being absorbed by major platforms |
"A policy is a starting point, not a finish line — and the gap between 'we have a policy' and 'we have the infrastructure to enforce it' is where most organizations are still working things out." — State of Martech 2026
AI Stack Doctor fills that gap. Free. In 90 seconds.
AI Stack Doctor follows the open source engine / hosted service model. The code is MIT — free forever. The cloud service is where the business value lives.
| Feature | Open Source (Self-Host) | Hosted Free | Pro Tier | Team Tier | Enterprise |
|---|---|---|---|---|---|
| CLI audit agent | ✅ Full | ✅ Full | ✅ Full | ✅ Full | ✅ Full |
| Basic PDF export | ✅ Full | ✅ Full | ✅ Full | ✅ Full | ✅ Full |
| Single audit run | ✅ | ✅ | ✅ | ✅ | ✅ |
| Self-hosted dashboard | ✅ Full | — | — | — | — |
| Audit history & trends | ✅ Self-hosted | — | 🔒 Pro | 🔒 Pro | 🔒 Enterprise |
| All 44 company profiles | ✅ Self-hosted | 10 profiles | 🔒 Pro | 🔒 Pro | 🔒 Enterprise |
| Agentic scheduler | ✅ Self-hosted | — | 🔒 Pro | 🔒 Pro | 🔒 Enterprise |
| Enhanced prescriptions | ✅ Self-hosted | Basic only | 🔒 Pro | 🔒 Pro | 🔒 Enterprise |
| Cohort filtering | ✅ Self-hosted | — | 🔒 Pro | 🔒 Pro | 🔒 Enterprise |
| Branded PDF export | ✅ Self-hosted | — | 🔒 Pro | 🔒 Pro | 🔒 Enterprise |
| API access | ✅ Self-hosted | — | 🔒 Pro | 🔒 Pro | 🔒 Enterprise |
| Team workspace | — | — | — | 🔒 Team | 🔒 Enterprise |
| White-label reports | — | — | — | 🔒 Team | 🔒 Enterprise |
| Custom company profiles | — | — | — | 🔒 Team | 🔒 Enterprise |
| SSO / SAML | — | — | — | — | 🔒 Enterprise |
| Gov Edition | — | — | — | — | 🔒 Gov |
| Dedicated CSM + SLA | — | — | — | — | 🔒 Enterprise |
Self-hosters get everything — you bring your own Anthropic API key and run your own server. That is the spirit of open source and we fully support it.
Hosted service users get a managed, always-on experience with cloud history, scheduling, and team features — without managing infrastructure.
Pro, Team, and Enterprise tiers are currently in development. Pricing and availability will be announced at launch. Join the waitlist to be first to know and get early access.
→ Join the Pro Waitlist → Register Government Interest
| URL | Description |
|---|---|
| ai-stack-doctor.onrender.com | Intelligence Dashboard |
| /guide | Non-Technical User Guide |
| /intake | Smart Client Intake Form |
| /legal | Legal & Privacy |
| /security | Security Posture |
| Feature | Description |
|---|---|
| 🎯 Smart Intake Forms | 4 persona-tailored forms — Consultant, Executive, Marketer, General |
| 💰 ROI Layer | Every recommendation includes gap cost, fix cost, projected ROI, payback period |
| 📖 User Guide | Beautiful non-technical landing page at /guide with research-backed stats |
| 🌍 44 Company Profiles | US, Europe, Asia, Latin America, Africa — including first-ever African AI benchmarks |
| 🔍 Cohort Filtering | Filter by industry (28 categories), size, and region |
| ⏱️ Agentic Scheduler | Autonomous audit scheduling, change detection, and alerts |
| 🔒 Security Foundation | Auth scaffolding, audit logging, Gov Edition roadmap |
| ⚖️ Full Legal Layer | GDPR, CCPA, EU AI Act, Data Processing Agreement |
| 📉 Deprecation Risk Intel | Flags tools at high risk of being absorbed by major AI platforms |
| 🔌 MCP Server Spec | Model Context Protocol server design — call audits from Claude/ChatGPT |
┌─────────────────────────────────────────────────────────────────────┐
│ AI STACK DOCTOR v4 │
│ ai-stack-doctor.onrender.com │
└──────────────────────────┬──────────────────────────────────────────┘
│
┌────────────────┼──────────────────────┐
│ │ │
▼ ▼ ▼
┌─────────────┐ ┌─────────────────┐ ┌───────────────────┐
│ / │ │ /guide │ │ /intake │
│ dashboard │ │ landing page │ │ 4-persona form │
│ .html │ │ guide.html │ │ intake_form.html │
└──────┬──────┘ └─────────────────┘ └────────┬──────────┘
│ │
▼ ▼
┌───────────────────────────────────────────────────────────┐
│ dashboard_server.py (Flask) │
│ │
│ 31 Routes across 8 categories: │
│ ├── Pages / /guide /intake /legal /security │
│ ├── Data /api/summary /companies /trend /compare │
│ ├── Intake /api/intake/submit │
│ ├── Auth /api/auth/generate-key /keys /revoke │
│ ├── Logs /api/audit-log │
│ ├── Lists /api/waitlist /api/gov-interest │
│ └── Sched /api/scheduler/* (10 routes) │
└──────────────────────┬────────────────────────────────────┘
│
┌────────────────┼────────────────────┐
│ │ │
▼ ▼ ▼
┌─────────────┐ ┌──────────────────┐ ┌───────────────┐
│ scheduler │ │ ai_stack_health │ │ SQLite DB │
│ .py │ │ _agent_v3.py │ │ history.db │
│ │ │ │ │ │
│ Classes: │ │ 6 Audit Tools: │ │ Tables: │
│ Agentic │ │ ├─detect_stack │ │ ├─ audits │
│ Scheduler │ │ ├─research │ │ ├─ alerts │
│ AlertEngine │ │ ├─integrations │ │ └─ history │
│ DigestEngine│ │ ├─governance │ │ │
│ ScheduleStore│ │ ├─redundancy │ │ Files: │
└──────┬──────┘ │ └─benchmark │ │ schedules │
│ └────────┬─────────┘ │ .json │
│ │ └───────────────┘
└──────────────────┤
│
▼
┌─────────────────────────────────────────────────────────┐
│ EXTERNAL SERVICES │
│ │
│ ┌──────────────────┐ ┌────────────────────────────┐ │
│ │ Anthropic API │ │ Search (configurable) │ │
│ │ Claude Sonnet │ │ ├─ DuckDuckGo (default) │ │
│ │ AI analysis │ │ ├─ Google Custom Search │ │
│ └──────────────────┘ │ ├─ Bing / SerpAPI │ │
│ │ └─ Private / Custom │ │
│ └────────────────────────────┘ │
└─────────────────────────────────────────────────────────┘
The audit agent uses a 6-tool agentic loop powered by Anthropic Claude:
User Input (company + mode)
│
▼
┌────────────────────────────────────────────────────────┐
│ AGENTIC AUDIT LOOP │
│ │
│ Tool 1: detect_ai_stack │
│ └─ 8 targeted searches across 7 domains │
│ GenAI/LLMs · Agentic · ML · Data Eng │
│ AI Platforms · MLOps · Cloud AI │
│ │
│ Tool 2: research_stack_health │
│ └─ Deprecations · vendor stability · G2 data │
│ + State of Martech 2026 deprecation risk intel │
│ │
│ Tool 3: check_ai_integrations │
│ └─ Pipeline health · data flows · observability │
│ │
│ Tool 4: audit_governance_and_ownership │
│ └─ 14 compliance frameworks + ROI context │
│ │
│ Tool 5: detect_redundancies_and_gaps │
│ └─ Capability overlaps · wasted spend │
│ │
│ Tool 6: benchmark_against_peers │
│ └─ 3-company comparison from 44 intel profiles │
│ │
└────────────────────────────────────────────────────────┘
│
▼
┌────────────────────────────────────────────────────────┐
│ REPORT OUTPUT │
│ │
│ Executive Summary + ROI Table │
│ Stack Inventory (confirmed tools) │
│ Deprecation Risk Flags (State of Martech 2026) │
│ Category Scores (7 domains / 100 pts) │
│ Category Deep Dives │
│ Governance & Compliance Health │
│ Peer Benchmarking │
│ Strategic Recommendations + Full ROI Analysis │
│ Enhanced Prescriptions with Priority Matrix │
│ Audit Confidence Summary │
│ │
│ Export: TXT · PDF (dark-themed) · Dashboard │
└────────────────────────────────────────────────────────┘
DOMAIN WEIGHT WHAT IT MEASURES
────────────────────────────────────────────────────────
GenAI / LLMs 14 pts Foundation models, RAG, fine-tuning
Agentic AI 14 pts Autonomous agents, orchestration
Machine Learning 14 pts Training frameworks, model lifecycle
Data Engineering 14 pts Pipelines, warehouses, feature stores
AI Platforms 14 pts Internal ML platforms, model serving
MLOps / LLMOps 14 pts Monitoring, observability, CI/CD
Cloud AI Services 16 pts AWS/GCP/Azure AI services maturity
────────────────────────────────────────────────────────
TOTAL 100 pts
🟢 Healthy 80–100
🟡 Needs Attention 60–79
🔴 At Risk < 60
Powered by State of Martech 2026 data (Brinker & Riemersma):
HIGH RISK — Being absorbed by ChatGPT / Claude / Gemini:
Jasper · Copy.ai · Writesonic · Anyword · Persado
Phrasee · Lately.ai · Lumen5 · Rytr
MEDIUM RISK — Major platforms building equivalent features:
Grammarly Business AI · standalone SEO AI writers
basic AI personalization engines
WATCH LIST — Categories under pressure:
Sales Automation point solutions (-23 net tools in 2026)
Social Media AI monitoring (-8 net)
Live Chat standalone AI (-23 net)
Video Marketing AI tools (-14 net)
Every audit now flags at-risk tools and estimates annual spend at risk from consolidation.
44 pre-loaded profiles across 5 regions and 28 industries:
Google · Microsoft · NVIDIA · Meta · OpenAI · Anthropic · Netflix · Tesla · Apple · Amazon · Mistral · Salesforce · Adobe · AMD · Oracle · Broadcom · Intel
Stability AI · DeepL · Synthesia · Aleph Alpha · ElevenLabs · DeepMind · Revolut · Adyen · Klarna · Wise
Baidu · ByteDance · Alibaba · Samsung · DeepSeek · Infosys · Ant Group · Paytm · Kakao
Nubank · Mercado Libre · Rappi · Clip · Ualá
Flutterwave · Safaricom (M-Pesa) · Moniepoint
🏆 First AI benchmarking tool in the world with African company profiles.
Critical: EU AI Act (2024) · GDPR+AI · US EO on AI · CCPA/CPRA · HIPAA+AI · China GenAI Regs
High: EU Data Act · Digital Services Act · NIST AI RMF · US State AI Laws · UK AI Regulation · ISO 42001 · PCI-DSS v4.0 · SOC 2
python3 --version # 3.11+
pip3 install anthropic ddgs rich flask reportlab gunicorngit clone https://github.com/dwnjuguna/AI-Stack-Doctor
cd AI-Stack-Doctor
# Get your API key at console.anthropic.com
export ANTHROPIC_API_KEY="sk-ant-..."
# Make it permanent (Mac/Linux)
echo 'export ANTHROPIC_API_KEY="sk-ant-..."' >> ~/.zshrc && source ~/.zshrcpython3 ai_stack_health_agent_v3.pypython3 dashboard_server.py
# Opens at http://localhost:5050# First send client to: http://localhost:5050/intake/consultant
# They fill the form and download intake_company.json
# Then run:
python3 intake_reader.py --file intake_acme.json --export bothai-stack-doctor/
│
├── 🤖 ai_stack_health_agent_v3.py # Main audit agent (CLI + API + 44 companies)
├── 📄 pdf_export.py # Dark-themed PDF report generator
├── 📋 intake_reader.py # Client intake → personalized audit runner
│
├── 🌐 dashboard_server.py # Flask backend (31 routes)
├── ⏱️ scheduler.py # Agentic scheduler (zero external deps)
│
├── 🎨 dashboard.html # Intelligence dashboard (44 companies)
├── 📝 intake_form.html # Smart 4-persona intake form
├── 📖 guide.html # Non-technical user guide
├── ⚖️ legal.html # Legal & privacy (GDPR/CCPA/EU AI Act)
├── 🔒 security.html # Security posture & Gov Edition
├── 🔌 MCP_SERVER_SPEC.md # MCP server specification (Q3 2026)
│
├── ⚙️ requirements.txt # Python dependencies
├── ☁️ render.yaml # Render.com deployment config
├── 🔐 .env.example # Environment variable template
└── 📚 README.md # This file
# Auto-created at runtime:
# ai_stack_history.db SQLite audit history & alerts
# schedules.json Agentic scheduler configuration
# audit_log.jsonl Append-only tamper-evident audit trail
# api_keys.json Pro tier API key store
# gov_interest.json Government Edition interest registrations
# intake_submissions/ Client intake JSON files
Send clients a tailored link before your first call:
| Persona | URL | Time | Best For |
|---|---|---|---|
| Consultant | /intake/consultant |
~10 min | Client engagements, gap analysis |
| C-Suite / Exec | /intake/executive |
~8 min | Board-ready reports, compliance risk |
| Marketer / CMO | /intake/marketer |
~7 min | MarTech AI stack, content AI audit, deprecated tool detection |
| General | /intake/general |
~5 min | Quick self-assessment |
The Marketer persona now includes a Content AI Stack Audit module — identifying tools at deprecation risk based on State of Martech 2026 data, and asking whether the stack is "AI everywhere, integrated nowhere."
Intake data = high-confidence ground truth. The agent uses it as primary source over web research.
Zero external dependencies — pure Python stdlib:
from scheduler import get_scheduler
sched = get_scheduler()
sched.start() # Starts background daemon thread
# Schedule weekly Stripe audit with Slack webhook
sched.schedule(
company = "Stripe",
mode = "competitor",
cadence = "weekly", # hourly/daily/weekly/monthly/quarterly
webhook_url = "https://hooks.slack.com/..."
)
# Trigger immediate on-demand audit
sched.run_now(schedule_id)
# Get change-detection alerts (fires when score moves 3+ pts)
alerts = sched.get_alerts()
# Get digest of all tracked companies
print(sched.get_digest())Every recommendation includes:
Gap Cost: $150K–$500K/year ← what inaction is costing
Fix Cost: ~$40K ← investment to resolve
Projected ROI: 350% / 12 months
Payback: 3 months
Quick Win: Enable LangSmith free tier this week — zero cost
9 ROI domains with evidence-based benchmarks: GenAI/LLMs · Agentic AI · Machine Learning · Data Engineering · AI Platforms · MLOps/LLMOps · Cloud AI Services · Governance · Redundancy
AI Stack Doctor will expose a Model Context Protocol (MCP) server — letting any enterprise using Claude, ChatGPT, or MCP-compatible agents call audits directly from within their AI workflow.
Tools planned:
run_audit → Full 90-second audit on any company
get_score → Latest score from history (instant)
compare_companies → Side-by-side 7-domain comparison
get_compliance_flags → 14-framework compliance risk check
list_companies → All 44 profiles with scores
get_deprecation_risks → Flag tools at consolidation risk
This will make AI Stack Doctor callable from Claude Connectors, ChatGPT Apps, LangChain, CrewAI, and any MCP-compatible agent framework.
See MCP_SERVER_SPEC.md for the full specification.
Context: The State of Martech 2026 report documents 29,000+ MCP servers built in 18 months — more than twice the entire martech landscape took 15 years to reach. This is a real distribution channel.
| Control | Status |
|---|---|
| HTTPS / TLS | ✅ Live |
| Public information only | ✅ Live |
| GDPR cookie consent | ✅ Live |
| Privacy policy + legal | ✅ Live |
| EU AI Act disclosure | ✅ Live |
| Private Server / Air-gap mode | ✅ Live |
| API key authentication | ⚙️ In Progress |
| Audit logging | ⚙️ In Progress |
| SSO / SAML | 📅 Planned |
| FedRAMP 20x | 🔮 Roadmap |
| CMMC 2.0 | 🔮 Roadmap |
Full posture → /security
Purpose-built for defense contractors and federal agencies. Separate infrastructure. Air-gap capable. AWS GovCloud. FIPS 140-2. NIST 800-171. FedRAMP 20x pathway.
- Fork this repo on GitHub
- Create a new Web Service on render.com
- Connect your GitHub fork
- Add environment variable:
ANTHROPIC_API_KEY=sk-ant-... - Build command:
pip install -r requirements.txt - Start command:
gunicorn dashboard_server:app - Deploy → live in ~3 minutes
# Start local API server
python3 ai_stack_health_agent_v3.py --api
# Run an audit via POST
curl -X POST http://localhost:8080/audit \
-H "Content-Type: application/json" \
-d '{"company": "Stripe", "mode": "competitor"}'
# Get audit history
curl http://localhost:8080/history
# List all tracked companies
curl http://localhost:8080/companiesContributions are very welcome! Priority areas:
- New company profiles — add to
COMPANY_INTELin the agent - New compliance frameworks — extend
GLOBAL_COMPLIANCE - New regions — Middle East, Southeast Asia, South Asia
- Local LLM support — Ollama / LM Studio integration
- MCP server implementation — see
MCP_SERVER_SPEC.md - Translations — guide.html in other languages
- UI improvements — dashboard, intake form, guide
git clone https://github.com/dwnjuguna/AI-Stack-Doctor
cd AI-Stack-Doctor
pip3 install -r requirements.txt
export ANTHROPIC_API_KEY="sk-ant-..."
python3 dashboard_server.pyMIT License — free to use, modify, and distribute.
Company names and trademarks referenced in audit reports belong to their respective owners. All scores are analytical estimates derived from publicly available information only. Not legal, financial, or professional advice. State of Martech 2026 data cited with attribution to Scott Brinker & Frans Riemersma.
- Anthropic — Claude AI powering the entire audit engine
- DuckDuckGo — Privacy-respecting default search
- Render.com — Hosting infrastructure
- Chart.js — Dashboard data visualizations
- IBM Plex Mono — Terminal typography
- Bebas Neue — Display typography
- Scott Brinker & Frans Riemersma — State of Martech 2026 research
- The open source community — for making tools like this possible
Built with ❤️ using the Anthropic Claude SDK
"I am because we are." — Ubuntu
Built with responsibility, ethics, dignity, integrity, and respect. Open source. Free forever. Global by design.
🌐 Live Demo · 📖 User Guide · 🔒 Security · ⚖️ Legal · 🐙 GitHub