Generative AI
AI & LLM Integration
I integrate large language models into real products — not demos. RAG pipelines, semantic search with vector databases and embeddings, LLM-based classification, and the engineering discipline to make generative AI reliable, observable and cost-aware.
I work in Python (FastAPI, LangChain, LangGraph) and wire AI features into existing web apps (Laravel, Vue.js). I tune hyperparameters like temperature and top-k/top-p, ground answers with retrieval, and add evaluation and guardrails so the same input gives dependable, repeatable results.
What I build
- RAG pipelines over your documents and data
- Semantic search with vector databases and embeddings
- LLM-based classification and extraction systems
- Fine-tuning, benchmarking and model comparison
- Deterministic, evaluated LLM features (temperature, top-k/top-p)
- AI features integrated into Laravel / Vue apps and APIs
Why work with me
I combine 15+ years of production web engineering with hands-on generative-AI R&D (currently as a Senior AI Solutions Engineer). That means AI features that actually ship, integrate cleanly and hold up in production — not proofs of concept that stall.
Frequently Asked Questions
Which models and tools do you use?
OpenAI and Anthropic APIs, LangChain / LangGraph, FastAPI, and vector databases such as Pinecone or pgvector — chosen per use case and budget.
Can you add AI to my existing app?
Yes. I integrate LLM features (search, chat, classification, automation) into existing Laravel, Vue.js or Python systems, with the back-end plumbing to support them.