Assistants and agents
Conversational tools and task agents grounded in your data, with guardrails on what they can see and do.
Practice 05 · AI solutions
AI features that still save time a quarter after the demo.
The demo is the easy part. We build the AI features that hold up once real people use them on real data with real stakes.
An AI feature is simple to demo and hard to trust. The first version dazzles in a meeting and then quietly hallucinates, or answers a question it shouldn't have had access to, or saves nobody any time because it doesn't fit the actual job. The gap between the demo and the daily tool is where most of these projects die.
We build for the daily tool. The assistant talks to your real data through your real permission model, and we measure it against the work it's meant to do rather than a handful of cherry-picked prompts. The concierge on this site is one small example of how we think about it.
The work, broken down
Retrieval (RAG)
Answers pulled from your documents and systems, with citations, so the model stops making things up.
Workflow automation
The repetitive internal work (triage, summaries, routing) handed to a model that's been measured on it.
Evaluation and guardrails
Test sets, monitoring, and limits so you know when the system is right and what it does when it isn't.
Four steps, one team
- 01
Find the real job
We pick a task where AI genuinely helps and the cost of a wrong answer is understood. Not a demo. A job.
- 02
Ground it in your data
Retrieval and permissions first, so the model answers from your reality and only sees what it should.
- 03
Evaluate honestly
We build a test set from real cases and measure accuracy, so 'it feels good' becomes a number you trust.
- 04
Ship with guardrails
Monitoring, fallbacks, and limits in place, then we tune it against how it performs in the wild.
What you leave with
Shipped, documented, yours to run.
- Assistant, agent, or automation in production
- Retrieval wired to your data and permissions
- Evaluation set and accuracy reporting
- Monitoring, logging, and guardrails
- A clear read on where it helps and where it doesn't
Eval Driven. Every feature measured against real tasks, not vibes.
1 Permission model shared between your app and the AI.
90d Still saving time a quarter after launch, which is the only test that counts.
Currently booking: Q3 2026
Have a brief that needs all five practices?
Send the rough version. Within a business day, you'll get back the questions we'd ask in a kickoff and an honest read on whether we're a fit. We don't need a deck to start the conversation.