AI features that make it to production — not just a demo that impresses once.
We build AI into real products: LLM-powered features, retrieval-augmented generation over your own data, agents and workflow automation, and integrations with leading providers like Anthropic and OpenAI as well as open-source models. The focus is on things that hold up with real users — evaluated, guardrailed and cost-aware — not a prototype that breaks on the second prompt.
Practical AI, not hype
Plenty of AI projects stall as impressive demos that never survive real users. We work backwards from a use case worth building, ship it behind evaluation and guardrails, and keep an eye on cost and latency — so what you launch actually gets used, not just screenshotted.
Part of full software engineering
AI isn’t a separate silo for us — it sits inside the same software engineering discipline as everything else we build. That means an AI feature ships with the same tests, architecture and maintainability as the rest of your product, so it doesn’t become a fragile corner no one wants to touch.
New studio, honest scoping
We’re a young studio, so we won’t oversell what AI can do for you. On a first call we’ll tell you which parts of your problem are a genuine fit for AI, which aren’t, and scope a small pilot you can evaluate before investing further.
Frequently asked questions
Which AI models and providers do you work with?
We're model-agnostic and choose per use case — leading providers like Anthropic and OpenAI, plus open-source models where self-hosting or data control matters. We recommend based on your accuracy, privacy and cost constraints, not a single vendor.
Can you add AI to our existing product rather than build something new?
Yes — most of our AI work is integrating features into an existing codebase and data. We start by finding the use case that's genuinely worth it, then build it behind proper evaluation so you know it works before it ships.
How do you keep AI features accurate and safe?
We ground responses in your real data with RAG, add evaluation and guardrails, and design for graceful failure. We're upfront about where a model is — and isn't — reliable enough to trust in production.
Ready to talk about ai engineering?
Tell us what you're building. We'll come back within one business day with an honest take and a plan.