Custom AI Tooling
Built for
your problem.
Off-the-shelf AI gets you to “neat.” Getting to useful usually means building something that knows your data, your rules, and your edge cases. That part doesn't come in a box, and it's the part we do.
The demo always works. The problem is everything after it — the questions your documents really get asked, the customer who phrases it sideways, the case where being confidently wrong costs money. Closing that gap is most of the work, and it's exactly what generic tools skip.
Your data beats a bigger model
A model that's read your contracts, your catalog, and your history is worth more than a smarter one that hasn't. Most of our work is getting the right context in front of it at the right moment.
We measure it
Before anything ships we build a test set out of real examples and score against it. “Feels better” isn't a result. You should know the hit rate and where it misses.
Swappable on purpose
Models change every few months. We keep the provider behind a seam so moving is a config change instead of a rebuild — a gateway, not a hard-wired SDK in forty files.
Agents that do the job
Not a chatbot. Software that takes a task, works through it with your tools, and comes back with it done — or a clear reason it stopped.
Retrieval over your documents
Search that answers in sentences and cites the page it came from. Built on your files, and current as they change.
MCP servers
Your systems exposed as tools an AI can actually use, so Claude and friends work from your live data instead of guessing about it.
Vision pipelines
Photos in, structured data out. Condition, category, contents, damage — whatever the picture is meant to tell you.
Evals and guardrails
The harness that proves today's change was an improvement, and the limits that stop it doing something expensive at 3am.
The hard example first
Bring us the case you think won't work. If we can't handle that one the easy ones don't matter — better to find out in week one than month four.
A thin slice, all the way through
One real workflow wired end to end and in front of real users fast. Depth before breadth, always.
Tune against real use
Once it's live, the questions it gets are the spec. We fold them back into the eval set and keep raising the floor.
If we get partway in and conclude the honest answer is a spreadsheet and two rules rather than a model, we'll say so.
A tool in production
Live, used by your team or your customers, and integrated with the systems it needs — not a notebook and a screen recording.
An eval suite
Real cases with known-good answers, scored on every change. It's how you'll keep improving it after we're gone.
The code and the prompts
All of it, in your repo. Prompts are source code and we treat them that way — reviewed, versioned, and explained.
A limits list
Where it's reliable, where it isn't, and what we'd never let it decide on its own. Worth more than a benchmark number.
