Enterprise AI Infrastructure
Self-Serve AI Infrastructure Kits
for Data-Sensitive Enterprises
Buy a kit. Follow the numbered instructions. Ship in days. No calls. No consultants. No vendor lock-in. Your data never leaves your own infrastructure.
Which problem are you solving?
Private Document Search
Law firms, auditors, logistics companies
Finding specific clauses in 5,000 PDFs takes hours of expensive human labour.
→ RAG KitAI Agent → Database Bridge
Tech companies, finance teams, operations managers
AI agents cannot query private databases without creating a security breach.
→ MCP BlueprintContract Data Extraction
PE firms, procurement teams, compliance officers
Clerks manually copy payment terms and renewal dates from hundreds of contracts.
→ RAG KitHIPAA/POPIA-Safe AI Search
Medical groups, accounting firms, architectural firms
Cannot use public cloud AI for patient records or confidential schematics.
→ RAG KitImplementation Kits
MCP Server Blueprint
Connect Claude, Goose, or any AI agent to your private database — securely
“Your AI agent is blind until you give it a window into your data.”
Companies want their AI agents to answer questions like "Which clients have unpaid invoices over 60 days?" — but pointing a public AI at a private database creates a catastrophic security hole. This kit gives you a complete, production-ready MCP server that acts as a read-only, SQL-validated firewall between any AI agent and your PostgreSQL or Supabase database.
How it works after you buy
Buy & download
Instant access to the complete codebase and step-by-step guide.
Add your DB connection string
Copy your Supabase or PostgreSQL URL into the .env file. Takes 2 minutes.
Deploy to Railway
One command. Railway free tier handles the hosting. Total cost: $0/month.
Paste the config into Claude Desktop or Goose
A 3-line JSON snippet is provided. Your AI agent is live.
What's included
- ✓Complete MCP server in TypeScript (Node.js)
- ✓Read-only SQL validation middleware — blocks any DELETE or DROP
- ✓Supabase + PostgreSQL + MySQL connection adapters
- ✓Claude Desktop and Goose config snippets (ready to paste)
- ✓Railway deployment guide (free hosting)
- ✓Security checklist (compliance-ready architecture)
- ✓Troubleshooting FAQ covering the 12 most common errors
RAG Implementation Kit
Let your team chat with 5,000 internal documents — without uploading them to ChatGPT
“The $3,000/month enterprise problem you can solve this weekend.”
Law firms, financial auditors, and logistics companies have thousands of disorganised PDFs and contracts. Their staff waste hours manually searching for specific clauses. They want AI-powered search, but uploading confidential documents to public models is a compliance disaster. This kit gives you a complete, private RAG pipeline — from raw documents to intelligent search — built entirely in your own Supabase database.
How it works after you buy
Buy & download
Full codebase, SQL schema, and illustrated step-by-step implementation guide.
Run the database schema
One SQL file creates the vector storage tables in your Supabase instance. 30 seconds.
Drop your documents
Run the Python ingestion script. It chunks, embeds, and stores everything into your private database.
Query in plain English
The included Next.js API route handles semantic search. Plug it into any front-end.
What's included
- ✓Complete Python ingestion pipeline (PDF, DOCX, TXT, HTML)
- ✓Supabase pgvector schema (SQL file — run once, done)
- ✓Next.js API route for semantic search (TypeScript)
- ✓OpenAI and Anthropic embedding adapters (bring your own key)
- ✓Pass-through architecture guide — zero data stored on our servers
- ✓GDPR / HIPAA / POPIA compliance configuration notes
- ✓Step-by-step illustrated guide (50+ numbered steps, no gaps)
- ✓Troubleshooting FAQ + private support email
Need something completely custom?
If your infrastructure is non-standard or you have a complex multi-system requirement, describe your setup in an email. We scope and build via async communication — no calls required.
Email Us Your Requirements →