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Make your coaching, learning, and care AI safe to ship.

You start with tested behavior packs and the eval set that scores every release, so quality is measured, not guessed.

What the work covers

Start wherever your product is today.

You leave with an asset you keep, whether that is a ranked risk list, a golden eval set, or an owned quality loop.

See the work on real products →
015 to 20 hours$1,500-$5,000

You need a fast, expert read

Working block

A focused block of senior time to pressure-test the product, surface the quality risks, and decide the next move. The quick way to start.

What it unblocks

You see what a security review or a serious buyer would find, while it is still cheap to fix.

The asset you keep

A ranked list of the quality risks and the one next step, written down.

022 to 4 weeks$8k-$20k

You need a runnable pack shipped

Pack buildout

We turn your method into a runnable Behavior Guidance Pack and stand it up in your eval stack, so every release is scored against your bar and you can prove the quality to a buyer.

What it unblocks

An evidence packet that clears your pilot or your enterprise review, with proof a clinician, a buyer, or a regulator can check.

The asset you keep

A golden eval set you keep, scoring every change against your bar and catching regressions before users do.

03Monthly$3k-$6k / mo

You need the bar to keep rising

Quality subscription

We keep your packs current, turn production failures into new tests, recalibrate the judges, and vet every new model against your bar before you switch.

What it unblocks

Your evidence packet stays current as scrutiny grows, and you learn whether a new model is better for your users before you ship it.

The asset you keep

A private test set that grows every month, the part a competitor can't copy.

04One-month cycles$8k-$18k / mo

You need your team to own it

In-housing program

A hands-on program that builds your eval and safety system alongside your team and trains them to run it, with a defined graduation so you finish independent.

What it unblocks

Your team owns the quality loop and can prove it to a buyer or an investor without an outside studio in the critical path.

The asset you keep

A trained team that runs the loop without us, and a pack you keep maintaining.

In build. Design partners open.

hunter-guard. The Behavior Guidance Packs, as an SDK your team installs.

The packs are already runnable. hunter-guard makes them a package that plugs into Langfuse and the rest of your eval stack, so the same scorers run against live traces and tie back to the outcomes you track, not only at build time. We are scoping it now with a design partner. Ask if you want to shape it early.

Join as a design partner

The first call is practical. We look at the product, the moments where a wrong answer costs you, and what's creating urgency, then recommend where to start or refer you on if we're not the right team.

Pressure-test my product

How the work runs

The loop behind every engagement.

You start ahead of a blank page. Our Behavior Guidance Packs bring tested rules and checks into step one, so your agent clears the bar sooner and your eval suite scores every release against it.

Explore the packs →
01

Define what good looks like

Turn your method into real scenarios, success criteria, and model answers, starting from our behavior library.

02

Test every change against it

Check every new version against that bar before it ships, so improvement is measured, not assumed.

03

Hold the line on risk

Set the boundaries, refuse what the agent should not answer, and route a crisis to a person.

04

Improve from real use

Turn each real failure into a new test and record what the advice led to, so you keep raising the bar.

Where we fit

Senior product judgment for AI in coaching, learning, and care.

You get a product lead who has built and shipped conversational AI, without hiring full-time or signing with a large agency.

Strong fit when

  • They want to win on how well the product handles its hardest user moments, not on price, lock-in, or who they know.
  • They're building conversational AI for coaching, learning, or care, where users or buyers have to trust the output.
  • They have a prototype, pilot, customer demand, expert methodology, or live product.
  • The experience needs to become more reliable, measurable, or ready for serious customers.

Not a fit

  • Competing mainly on price, distribution, or lock-in, where specialized quality is not what wins the deal.
  • Looking for a low-cost development shop.
  • One-off prompt writing, or automation where quality and trust aren't the hard part.
  • Broad AI education for a team that hasn't identified a real product problem yet.

Not there yet? Where to start instead →

Common questions

What teams ask before they reach out.

The system around the model. Conversation architecture, golden eval sets, refusal and escalation rules, memory design, and an improvement loop where you turn every real failure into a new test. You leave owning the standard, the evals, and the loop, the assets that keep a specialized product ahead as the underlying model changes.