Denys M.

I help companies move from AI prototypes to reliable production systems. My focus is building solutions that handle real-world traffic, edge cases, and scale, not just impressive demos. What I Build AI Agents and Automation As an AI agent developer, I create custom agents for customer service, document processing, and workflow automation. This includes multi-agent architectures, tool design, memory systems, and policy controls using LangChain and similar frameworks. LLM and GPT Integrations Production-grade ChatGPT integration with cost optimization, error handling, and fallback strategies. I've helped clients reduce OpenAI API costs by 60-70% while maintaining or improving output quality. API Integration with Business Systems I connect AI agents to CRMs, ERPs, and workforce tools. Experience with Bitrix24, HubSpot, When I Work, and custom API integration with existing backends including Laravel and other frameworks. RAG Systems Knowledge bases that actually return accurate answers. Vector databases (Pinecone, Weaviate, FAISS), chunking strategies, retrieval tuning, and evaluation pipelines. Backend Infrastructure As a Python AI developer and machine learning developer, I build the async processing, queue systems, and infrastructure needed to serve AI at scale using FastAPI and modern Python patterns. Recent Project Outcomes - E-commerce: Product search AI agent with 47% conversion improvement - Healthcare: Medical image processing at 100k images/day with 92% accuracy - Financial services: RAG document analysis reducing processing time from 6 hours to 6 minutes - Logistics: Delivery optimization with 73% reduction in failures Problems I Help Solve - ChatGPT integration that works in testing but fails under production load - AI agent development projects stalled after POC phase - OpenAI API costs growing faster than value delivered - RAG systems returning irrelevant or hallucinated answers - API integration between AI systems and existing business tools - Need a Python AI developer to rescue an existing codebase How Engagements Work - Week 1-2: Audit current system, identify bottlenecks and quick wins - Week 3-4: Architecture design and core AI agent development - Week 5-6: ChatGPT integration, API integration, optimization, testing - Week 7-8: Deployment, monitoring, documentation, team handoff I work well with product managers and technical leads to align AI development with business goals. Engagement Options - Rescue/Fix: Stabilizing existing ChatGPT integration or AI agent systems - Build New: End-to-end AI agent development from requirements to production - Advisory: Ongoing Python AI developer support and code review Background - 50+ production AI systems deployed - Core expertise: Python, LangChain, multi-agent systems, RAG, GPT/OpenAI/Anthropic APIs, vector databases - I prioritize clear documentation, maintainable code, and measurable outcomes What Clients Say "Delivered a working system in 6 weeks that's now generating significant revenue. Refreshingly practical approach to AI agent development." - CTO, Series B SaaS "Best ChatGPT integration work we've seen. Helped us move from concept to production faster than expected." - VP Innovation, Fortune 500 Technical Stack Python, FastAPI, LangChain, LlamaIndex, OpenAI API, Anthropic, AWS Bedrock, Pinecone, Weaviate, FAISS, Docker, AWS/GCP/Azure, PostgreSQL, Redis Next Step If you're looking for a Python AI developer to build or fix your AI agent systems, send a brief description of your project. I'll review it and share honest feedback on approach, timeline, and fit. Currently booking for June. Limited to 3 active AI agent development projects.