Service
AI Engineering
We help teams move generative AI beyond demos into dependable products — retrieval-augmented systems, agentic workflows, and AI features integrated into your stack, with the evaluation and guardrails needed to run them in production.
What we do
- Retrieval-augmented generation (RAG) systems
- Agentic workflows and tool-using assistants
- LLM fine-tuning and prompt optimization
- Evaluation harnesses and quality guardrails
- Inference cost & latency optimization
- Integration of AI into existing products and data platforms
What you get
- A production AI feature or service with an evaluation suite
- Retrieval / data pipelines feeding your AI system
- Guardrails, monitoring, and cost controls
- A clear path from prototype to scale
Tech we use
PythonLLM APIsVector databasesLangChain / LlamaIndexRAGDatabricksEvaluation frameworks
FAQ
How do you keep generative AI reliable?
We treat evaluation as a first-class deliverable — building test sets and automated evals so changes are measured, not guessed, before they reach users.
Can AI build on our existing data platform?
Absolutely. The best AI products are grounded in your own data. Our data and ML engineering work means we can build the full pipeline, not just the model call.
Have a data, ML, or AI challenge?
Book a 30-minute call. We'll tell you straight whether and how we can help.
Book a meeting