AI & Data

We bring LLMs, retrieval, and automation into real products — and make them reliable enough to ship.

LLM featuresRAG / retrievalEvalsPipelinesRecommendationAutomation

We bring LLMs, retrieval, and automation into real products — scoping what is worth building, wiring up evals, and shipping features that hold up in production rather than in a demo.

The gap between an impressive AI demo and a feature you can put in front of users is mostly engineering: retrieval that returns the right context, evals that catch regressions, guardrails, and a data pipeline that doesn't fall over. We help you scope what's actually worth building, then build it so it holds up under real traffic and real edge cases.

What we do

LLM product features

Assistants, generation, extraction, and classification built into your product with the prompting, tooling, and fallbacks to make them dependable.

RAG & retrieval

Grounding models in your data — chunking, embeddings, vector search, and ranking that actually surface the right context.

Evaluation & quality

Eval suites and monitoring so you can change a prompt or model and know whether quality went up or down.

Data pipelines

The ingestion, transformation, and automation underneath — reliable plumbing so the smart features have clean data to work with.

What you get

Production AI features integrated into your product
A retrieval / RAG system grounded in your own data
An evaluation harness and quality monitoring
Data pipelines for ingestion and processing
Documentation and a team that understands what was built

Common questions

We have an AI demo that works but can't ship it — can you help?

That's exactly the gap we close. Getting from demo to production is about retrieval quality, evals, guardrails, latency, and cost — the engineering around the model. We specialize in making AI features dependable enough to put in front of real users.

Which models and providers do you use?

We're not locked to one. We choose based on your needs — quality, latency, cost, privacy — and build so you can switch models without rewriting the product. We default to the most capable current models and keep the integration portable.

How do you keep AI features from regressing?

Evals. We build evaluation suites and monitoring so every prompt, model, or pipeline change is measured against real examples — no shipping on vibes.

More of what we do

Have a ai & data project in mind?

Tell us what you're building. We'll tell you honestly how we'd approach it — and whether we're the right team for it.

Start a project