AI Systems in Production
I take your POC to production without collapse or blowing your budget. I build robust AI architectures optimized for cloud costs and scalable from day one. Beyond pretty demos, I deliver systems that handle real traffic.
Production-Ready RAG
Full implementation: embeddings, vector databases (Pinecone, Weaviate, pgvector...), chunking strategies, and optimized retrieval. System ready to scale.
Fine-tuning & Optimization
Fine-tuning models (OpenAI, Llama, Mistral...) for specific use cases. Prompt optimization and cost reduction up to 60%.
Agent-based Systems
Multi-agent architectures with LangChain, LangGraph, CrewAI, and others. Agents that reason, use APIs, and execute complex workflows autonomously.
Cloud & Infrastructure
Deployment on AWS, GCP or Azure. Serverless, containers, or VMs depending on your needs. Includes CI/CD, observability, and rate limiting.
Cost Optimization
Intelligent caching, model routing, batch processing. Typical savings: 20–60% on API costs.
Evaluation & Testing
Automated evals with real datasets. Quality, latency, and cost metrics. Regression testing before each deployment — no surprises in production.
How I Work
Week 1–2: Architecture & Setup
Design of a technical architecture tailored to your use case. Setup of cloud infrastructure, repos, CI/CD and monitoring tools. Technical stack defined and documented.
Week 3–5: Core Implementation
Building the AI system: RAG pipelines, fine-tuning, agents, or the components you need. Integration with your existing backend/frontend. Continuous testing with real data.
Week 6–7: Optimization & Testing
Optimization of prompts, costs and latency. Automated evals and regression testing. Load testing to confirm scaling. Complete technical documentation.
Week 8: Deployment & Handoff
Production deployment with rollback plans. Monitoring and alerts configured. Handoff session with your team: code review, architecture walkthrough, and best practices for maintenance.
Want to implement AI automations? Is your POC stuck for months? Not sure it will scale? API costs blowing up? In 4–8 weeks you have a production-ready system that works, scales and stays within budget.