I build autonomous multi-agent AI and intelligent automation workflows.
Founder of Crypto Champion Zone with over 2 years of experience architecting LLM integrations, RAG pipelines, and complex automation systems on AWS and Supabase. I don't just write code—I replace manual operations with scalable, reliable AI systems.
OpenAI, Anthropic (Claude), Google Gemini, OpenRouter. Designing multi-agent systems, RAG pipelines, and prompt caching strategies.
n8n, Zapier, Make. Turning messy, manual processes into clean, automated pipelines.
Node.js, TypeScript, AWS (EC2), Supabase (Edge Functions, Postgres). Robust API integration.
Problem: Manual orchestration across research, planning, building, and verification creates bottlenecks.
Solution: 8-agent autonomous system on AWS (Node.js + Anthropic API). Central CEO orchestrator delegates to 7 specialized agents. Integrated with Langfuse and mem0.
Impact: Production-deployed on AWS Elastic IP with PM2 process management. Telegram bot interface remained operational through regional AWS issues. Architecture designed to consolidate multi-person coordination workflows into a single autonomous stack.
Problem: AI-generated financial summaries hallucinate. Single-model outputs cannot be trusted.
Solution: n8n workflow fetching CoinGecko data. OpenAI generates summaries, then Gemini independently verifies them against raw data before Supabase insertion.
Impact: Reusable "Two-Model Verification" pattern that catches hallucinations before hitting production.
Problem: Retail investors struggle to parse complex SEC filings and FDA medical supply chain data.
Solution: RAG system on Supabase Edge Functions using Claude. Parallel queries across 3 tables with 10-turn memory and prompt caching.
Impact: ~90% input-token cost reduction via Anthropic prompt caching. Cost per turn ~$0.01–0.03 at Sonnet 4 pricing. Endpoint live, JWT-authed, and verified working end-to-end.
Problem: Investors in unstable and frontier markets make emotion-driven decisions under pressure and quietly rewrite their own thesis after a trade goes wrong. There is no tamper-proof record of what they actually believed when they made the call.
Solution: A "Think → Plan → Lock" workflow where users define thesis, risks, and exit triggers, then SHA-256 hash the plan so future-them can't revise it. Multi-auth via email, MetaMask (Ethereum), and XUMM (XRPL) with cryptographic signature verification. Observational AI overwatch (Mega Scout, Perplexity-powered) flags risk events above threshold without giving advice. PWA-installable with offline support; Supabase Row-Level Security across all user data.
Impact: Decision-integrity architecture — plans become immutable receipts of intent via cryptographic hash. Structurally non-advisory by design, reducing liability exposure while preserving operational utility. Architecture includes freemium/premium tiering, role-gated admin panel, Resend email integration, and offline-first PWA installable UX. Built in Lovable; pending public deployment.