AI automation
Replace repetitive sales, support, and ops work with agents that still know when to ask a human.
ExploreFind out if the product should use AI at all.
Founders skip this and jump to screens. We map the job, the user, the model, and the failure cases — then write a brief you can actually build from.
Teams we have designed and built for
The questions we refuse to skip
Discovery is a set of decisions, not a workshop photo.
Should AI exist here?
If a rules engine or a better form does the job, we say so.
What does the model do?
Generate, retrieve, classify, route — named, not 'magic'.
What does the human do?
Approve, override, take the call, own the relationship.
How do we know it failed?
Evaluation, sampling, and a path to undo — before you scale traffic.
You walk away with
A brief, not a graveyard of Figma frames.
01
Problem and user
Who hurts, how often, and what they do today instead.
02
AI / human split
Permissions, confidence, and when the system must ask.
03
First experiment
What to build, how to measure it, what would kill the idea.
Bring the idea. We will pressure-test the AI.
A 15-minute call is enough to know if discovery is the right first engagement.
FAQs
How working with us actually goes
Start with a 15-minute call. If it is a fit, you get a written next step — scope, timeline, and investment — not a leftover pitch deck.
We still talk to users and write a brief. We also decide what the model is allowed to do, how you will know it is wrong, and whether AI is even the right tool.
A written product direction, a split of AI vs human jobs, failure cases, and a first experiment — not forty screens.
Then that is the deliverable. We would rather kill a bad AI idea in discovery than decorate a chatbot nobody trusts.