For conversational AI teams in coaching, learning, and care

Make high-stakes AI guidance reliable enough to scale.

We build the eval sets, boundary rules, and escalation paths that catch a wrong answer before a parent, a patient, or a regulator does.

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A short call. We look at your biggest quality gap and give you a straight read on closing it. No code or data access needed.

Trusted by teams building coaching, learning, and care products people rely on.

Beyond the model

Your edge is the eval set and boundary rules you keep.

Anyone can call the same model you do. What lasts is the eval sets, the boundary rules, and the conversation design you own.

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You're probably in the right place if

Users love it, and that's the only proof you have.
Early sessions look great, and nothing yet shows a buyer that the quality holds on the thousandth conversation.
The pitch promised safer AI.
You raised on a safety story, and the eval system behind it is thinner than the deck.
People still read the transcripts.
A human review team is the quality control, and message volume is outrunning it.
A new model just shipped.
You want it to lift your product, not leapfrog it, and nothing scores the difference.
Someone is about to look inside.
An enterprise buyer, a clinician, or a regulator wants to see how a wrong answer gets caught.
The expert can't review every reply.
The method lives in a licensed expert's judgment, and the product has to hold their bar without them.

Pressure-test my product

Earlier than that? See where to start.

How we help

The three problems teams hire us for.

Bring us in as a one-off diagnostic, an outcome-defined sprint, or a standing partner on your roadmap.

Your product is live

A quality system, not more reviewers.

An eval suite that scores every answer against your bar, a gate that catches the regression on every model change, and a loop that turns each failure into a permanent test.

Starts as a diagnostic of your riskiest conversations. The suite ships in a sprint.

You made a safety claim

Build the system that backs it.

Escalation paths, refusal rules, and release gates, with evidence a clinician, an enterprise buyer, or a regulator can check.

A sprint builds the proof. A standing partner keeps it current as scrutiny grows.

An expert's method is the product

Turn the method into behavior you can test.

The method written down as conversation design and scored examples, so the product holds the expert's bar without them reading every reply.

Starts as a working session with your expert. A sprint makes the method testable.

How we come in

One-off advisory diagnostic

A working block of senior hours to name the quality risks and pick the next move.

Outcome-defined sprint

Two to four weeks to ship one defined outcome, like your first eval suite.

Standing partner

A monthly seat alongside your team on the roadmap, the eval suite, and every release.

Pressure-test my product See how each engagement runs →

What you own when the work is done.

Conversation design, the eval set that scores every change, the rules your agent won't break, and the loop that turns each failure into a new test. You own all of it.

See what compounds →

Conversation architecture

Where your coach decides to push, back off, or hand the user to a person.

Golden eval sets

Scored example answers that catch a regression before a model change ships.

Safety & boundary systems

What your agent refuses, and when it tells a user to call a doctor.

Improvement loops

A weekly routine that turns each failure into a test that stays in the suite.

Knowledge structures

The expert method written down, so it runs past the few people who hold it.

Exploring · on request

Pre-production rehearsal. For agents that take real actions, we can rehearse against a copy of your real setup before launch, so problems show up in testing, not in front of users. An emerging capability, offered on request.

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Behavior Guidance Packs

Start with the moments where a wrong answer loses the user.

Every build starts from a ready-made set of those moments, like spotting a crisis or refusing medical advice, each with the checks to test it. We tune it to your product, so your first eval suite is days in, not months.

Explore the packs →

Example behavior packOne example, for guidance products

Reflect before advising
The user arrives activated. The agent steadies the moment before it reaches for a fix.
Ask one good question
When more is unknown than known, the agent opens the right door instead of filling the silence.
Stay non-defensive on hard topics
On contested ground, the agent helps a person think instead of winning the argument.
Escalate without abandoning
When a moment turns risky, the agent shifts into support without going cold or robotic.
Report progress, protect privacy
The agent shows a sponsor that it's working without exposing what was said in confidence.

What we've built

Avani's coach learned when to stop and tell a parent to call a doctor.

All case studies →

askavani.com

Coaching & relational AI · Avani

A coaching AI that knows when to stop coaching

Conversation architecture, memory the user controls, refusal and boundary behavior, and evals tuned for tone and steadiness.

Read the case study →

supplierkit.com

Operational decision-support AI · SupplierKit

An ops AI a coordinator can put in the workflow

A human-in-the-loop verification workflow, a durable system of record, and readiness monitoring that flags what's expiring.

Read the case study →

David Meehan

Founder, Hunter Green

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Build what compounds.

Most teams have plenty of ideas and weak signal on which ones matter. Let's find where your team should be focusing on the user experience that general purpose tools can't compete with.

I've led product at startups and large, compliance-heavy companies. Hunter Green is the studio I run to build conversational AI that users can trust.

Pressure-test my product More about the studio →