About Services Work Generative AI Clients Team Insights Careers Contact

Generative AI

AI features that work in production, not just in demos.

Most AI prototypes never survive contact with real users, real data, and real operational scrutiny. Our practice exists to bridge that gap — building the unglamorous infrastructure that turns a clever notebook into a system your team can actually rely on.

Our AI practice

Three pillars of how we build with AI.

We've been working with large language models since the first GPT-3 betas. The lessons we've drawn show up in every engagement.

/ 01 — Retrieval first

Grounding before generation

Almost every useful AI feature lives or dies on what gets retrieved before the model sees the prompt. We invest heavily in chunking strategies, hybrid search, and the evaluation harnesses that tell you when retrieval is silently failing.

/ 02 — Agents, carefully

Boring tools, real boundaries

We build agents with explicit state, narrow tool surfaces, and human-in-the-loop checkpoints where they matter. Our preference is for agents that do one thing dependably, rather than ones that try to do everything and occasionally embarrass themselves.

/ 03 — Eval-driven

Test like it's software

If you can't measure it, you can't ship it. Every AI feature we build comes with a test set, an evaluation harness, and a clear answer to the question "how do we know this didn't get worse this week?"

What we build

The shapes our AI work usually takes.

Knowledge Copilots

Internal copilots grounded in your documents, with audit trails and role-based scoping built in.

Workflow Agents

Agents that automate well-defined operational workflows — with state, retries, and human approval steps.

Document Processing

Extraction, classification, and structured output pipelines that beat traditional OCR-plus-rules architectures.

Conversational Interfaces

Chat surfaces with memory, tool use, and the safety scaffolding to deploy them in customer-facing contexts.

Evaluation Frameworks

Custom eval harnesses that catch regressions, measure quality, and let your team ship AI changes confidently.

Model Routing

Orchestration layers that pick the right model for each request, balancing cost, latency, and quality.

Multilingual Pipelines

Retrieval and generation pipelines that handle non-English content as a first-class concern, not an afterthought.

Safety & Guardrails

Input/output guardrails, prompt injection defense, and policy enforcement that holds up in adversarial settings.

Let's build

Have an ambitious idea? We'd love to hear it.

Whether you're testing a hypothesis or scaling an established product, we'd be glad to spend a half-hour helping you think through the next step — no pitch deck required.