PITTECHS / FOR FOUNDERS AND PRODUCT TEAMS

Evals, traces and guardrails for the AI feature you already shipped.

For founders and CTOs at companies of one to fifty people. One live feature, no AI engineer on staff, and nobody's procurement process to clear.

You have an LLM or agent feature in front of real users and no reliable way to tell when it gets worse. Send us the build. Five business days from access you get a written engineering review of that flow: what breaks, why it breaks, and what to fix first.

One flow, one written review, five business days from access. Reviews start at $500, fixed price agreed in writing before any work starts.
No embedded team. No monthly minimum. No call required before you get something in writing.

pittechs.com · ai build review

read one flow, its prompts, its tools, its data

evals what quality is, and when it drops

guardrails the actions a model must never take alone

report what breaks, why, and what to fix first

What we build

Three things we build after a review, in the order they usually matter

Evals and traces around a feature that is already live.

Right now you cannot tell the difference between a bad day and a regression. We build the eval set that defines what good means for your flow, and the tracing that lets you explain a specific bad answer after a customer reports it.

Retrieval that cites a real source.

A RAG system returning weak answers, or confident answers with nothing behind them, is usually a retrieval problem dressed as a model problem. We rebuild it so every answer carries the document and the passage it came from and can be checked instead of trusted.

Guardrails and deterministic checks around the actions you cannot undo.

Your agent can send, delete, charge, or commit. Judgment about whether it should is a model's weakest skill. We put deterministic gates in front of those actions, so the irreversible ones need something more than a confident sentence.

Why not a consultancy, a freelancer, or a hire

The three other ways to solve this, and what each one costs you

An AI consultancy.

The good ones are genuinely good, and they are built for a different customer. Their model is a team embedded in your repos for months, which means a monthly minimum, a scoping call before anyone tells you anything, and a company big enough to put outside engineers through onboarding, SSO and a security review. If that is you, hire them - honestly, you should. If you are fifteen people with one broken feature, the problem is not that you cannot afford them. It is that you are not the customer they are built to serve, and a firm that runs a bench has to fill it with engagements bigger than yours.

A freelancer.

Plentiful, cheap, and mostly prompt engineers. Prompting is the half of this work that is not scarce. Auth, evals, tracing, monitoring, failure handling and deterministic gates around the actions a model should never be trusted with - that is the half that decides whether the feature survives, and it is a different skill set from writing a good prompt.

A senior AI engineer on staff.

The right long-term answer and the wrong short-term one. Senior AI hires are taking months, cost six figures, and the gap compounds every week the role is open. A fixed-scope review is not a substitute for that hire. It stops the problem growing while you make it.

What we are.

A senior engineer scopes your work, is the one you talk to, and is accountable for delivering it. One fixed price agreed before the work, one written deliverable five business days from access. No embedded team, no monthly minimum, and nobody junior working behind a senior name. You get less capacity than a consultancy and more judgment per dollar than you can currently hire.

Objections

Fair questions

"How is this different from an agency audit?"

Mostly size and shape. An agency audit is usually the front end of a larger engagement, scoped by people who will not do the work and priced accordingly. This is a fixed-fee piece of engineering written by the person who would do the fixing, with no obligation to buy the fixing. If the review says the cheapest good answer is something we do not sell, it will say that.

"Can you work in our stack?"

Probably, and if not we will say so before you pay. Tell us what it is in the form. A review that needs a stack we do not know well is a review we will decline rather than fake.

"What if you look at it and it is actually fine?"

Then you get that in writing, with the reasons, and you keep your money for the build instead of a rescue. We would rather tell you that once than sell you a fix you did not need.

The questions about the missing case studies, the missing name, walking away, and your data are answered on the home page.

Data boundary

How your data is handled

  • Send only what you are comfortable sending. No passwords, API keys, access tokens, health records, financial account data, or confidential customer records in the form.
  • Read-only access and your exported prompts are what start the five days, and they are also the whole of what we ask for.
  • Handling boundaries in writing before anything sensitive moves. We sign an NDA on request.
  • Your repository, your infrastructure. Nothing proprietary in the middle and nothing to be locked into.
  • Two things we will not build, on any budget. A system that makes the final decision in a medical, legal, hiring, lending or insurance context, because software can prepare a decision and a person takes it. And anything running on regulated records before a signed scope and written handling boundaries.

Send us the build.

Tell us what exists today, where it breaks, and what your users actually need. That is enough for us to quote.

Start a Build Review

One flow, one written review, five business days from access. Reviews start at $500, fixed price agreed up front.
No secrets, credentials or confidential records through this form.