AI & ML Engineering
Classical ML and GenAI engineered for production. Data, models, retrieval, orchestration, and guardrails come together so intelligence ships reliable, not experimental.
- Model
Streaming generation with tool use, retries, and structured outputs, plus latency budgets and fallbacks built into every request path so model choice stays flexible as your product requirements evolve.
- RAG
Embeddings and retrieval over your own verified source of truth, with chunking, ranking, and filters tuned for answer quality so responses stay grounded and auditable back to source documents.
- Output
Eval gates and tracing before anything reaches production users, with safety, cost, and latency controls dialed for live traffic and regression checks that keep answer quality steady as you ship.
- LLM integrations with tool use, streaming, and structured outputs ready for scale
- RAG pipelines grounded on your data with measurable retrieval quality
- Evals and tracing in place before regressions ever reach users
- Cost, latency, and safety controls tuned for live production traffic