AI Integration
AI that works in production, not just demos
I build AI features that handle real traffic — RAG pipelines, multi-agent systems, streaming responses, proper error handling. Systems that convert users, not just impress in a pitch.
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RAG Pipelines
Document ingestion, chunking, embedding, and retrieval. Your AI answers questions using your actual data.
Multi-Agent Systems
Orchestrated AI agents that route, plan, and execute complex workflows autonomously.
LLM Routing
Dynamic routing across Claude, GPT-4, and Gemini based on task complexity, cost, and latency requirements.
Streaming & Caching
Real-time streaming responses with intelligent caching to reduce costs and improve response times.
Production Error Handling
Graceful fallbacks, retry logic, rate limit management, and monitoring. No crashes in production.
Vector Databases
Pinecone, Weaviate, or pgvector — I choose the right vector store for your scale and use case.
Need AI that actually converts?
I took Sanofi from 72% to 96.2% accuracy. I automated 700K+ monthly interactions for Wizz Air. Let's talk about your use case.
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