AI you can prove actually works

Automate the work that eats your week.

AI consulting and custom agent development, one workflow at a time, with a pass/fail test you can run yourself.

Most AI tools look great in the demo and drift once real work shows up. We agree the test before we build, write it into the contract, and hand you the engine that runs it. If it fails, you do not pay the balance.

Fixed scope, fixed price, from $5,000. Your code in your repository. No retainer.

cadagent.reviewHC-01 v2 · 2026-07-16
Review gate results for HC-01 v2 · 2026-07-16, produced by cadagent.review
G1printed parts fit build volumePASS
G2every mate verifiedPASS
G3body / display no overlapmeasured 649.18 mm³FAIL
G4display / retainer no overlapmeasured 2067.83 mm³FAIL
G5body / retainer clearancemeasured 0.0 mmFAIL
G6every part fastenedplug floatingFAIL
verdictFAIL2 of 6 gates

A real review from our own work: an early HC-01 enclosure, failed on four measured rows before it was fixed. Every build includes the engine that runs a review like this.

The work isn’t hard. There’s just too much of it, and it all runs through one person.

Sound familiar?

  • Requests for quote wait in an inbox while someone retypes the specs into a quote.
  • Orders, invoices or inspection results get copied from one system into another by hand.
  • An AI tool got tried, looked good for a week, and now nobody can say whether it’s still right.

The last one is common. By Gartner’s June 2025 forecast, half of the companies planning to cut customer service staff with AI will drop those plans by 2027. In our view the build is rarely what breaks. It’s that nobody can say, without an opinion, whether the thing is still working.

Three passes, and the third one has no idea what the first two did.

This is the architecture behind every system we ship. It exists because the expensive failures are never the ones you thought to test for.

  1. 1

    Maker

    Builds the thing

    An agent writes the implementation against your spec — the workflow, the integration, the pipeline. Ordinary work, done fast.

  2. 2

    QA engine

    Runs the assertions

    A deterministic script, not a model opinion. Every criterion we agreed is a row that returns PASS or FAIL with a measured value. Same input, same verdict, every time.

  3. 3

    Independent reviewer

    Asks whether it would really work

    The engine can only check what it was told to check. So a separate reviewer, given no knowledge of how the thing was built, looks at the result and answers one question from first principles. It catches the failures nobody wrote an assertion for.

You get the engine, not just the verdict. It runs in your CI, on your machine, after we are gone — so “it still works” is something you can check rather than something we assert.

We built three of these for our own work first.

Each has run end to end on our own work. Each has a review engine that can fail it. The last one has never approved a product, which is the point.

Hardware design pipeline

7 agents

Takes a parts list and functional intent, returns a fab-ready 2-layer PCB, a printable enclosure fitted to it, and ESP-IDF firmware wired to the board's own pinout.

Every purchased electronic part must be modeled from real geometry: a vendor STEP or a model built from measurements. A placeholder box fails the review unless it carries a written waiver.

Video delivery pipeline

3 agents

One 360° master in; a widescreen cut, a vertical cut, the 360 file, stills, a 360 player and setup instructions out, unattended: it claims a job from a queue, plans the camera moves, renders, checks its own output, then publishes a hosted tour.

The check measures whether the vertical cut was framed independently — a center-crop of the widescreen fails, even though it looks fine.

Product research pipeline

5 agents

Researches a market, prices a product against its real page-one competition, and recomputes the margin from cost inputs rather than trusting the claim.

Nine deterministic gates. Across seven cycles, 48 candidates: none reached GO, 46 were killed with the measured reason, 2 are parked.

Fixed price, and you know the test before we start.

No discovery retainer, no hourly billing, no scope that grows after the invoice. You see the price here so you can decide whether to talk to us at all.

One workflow, verified

One process that eats hours every week, automated end to end, with the test that proves it works.

$5,000

2–3 weeks

  • Written pass/fail criteria, agreed before any code is written
  • The implementation, in your repository
  • The review engine that runs the criteria, yours to keep
  • A working handoff session and 30 days of fixes

Production build

Several connected processes running on the systems you already use, with logging and alerts when something goes wrong.

from $10,000

4–8 weeks

  • Everything in the single workflow engagement
  • Integration across your existing stack
  • Failure handling and alerting you can actually read
  • The gate wired into your CI so it runs on every change

If it misses the criteria, you do not pay the balance.

Half up front, half on delivery. If the gate we agreed does not pass, the second half is not owed and you keep the work so far. We would rather carry that risk than argue about whether something is finished.

Book a 15-min call

Questions people ask before booking.

What does an AI consulting engagement cost?
A single verified workflow is $5,000, delivered in two to three weeks. A production build across several workflows starts at $10,000 and runs four to eight weeks. Both are fixed price — the number does not move after we agree the scope.
How is this different from hiring an AI developer on a freelance marketplace?
Price, mostly, and what you get for it. A freelancer will build the automation for a few hundred dollars and hand you a working demo. What you will not get is a written definition of correct, or an engine that checks it. If your automation touches real customers or real money, a silent failure is expensive. Closing that gap is what you are paying for.
What does verified actually mean here?
Before any code is written we agree the criteria in writing — specific, measurable statements about what the system must do. Those become rows in a review engine that returns PASS or FAIL with the measured value. It is a script, not a judgment call, so it gives the same answer every time and it runs after we are gone.
What happens if the gate fails?
We fix it, or you do not pay the balance. Payment is half up front and half on delivery, and the second half is contingent on the criteria passing. You keep whatever has been built either way.
Do you work with n8n, Zapier, Make and our existing tools?
Yes, and often the right answer is to use them. Those platforms are good at connecting things. They are weak at proving a multi-step process did the right thing when nobody was watching, which is the part we add.
Will you sign an NDA before we share anything?
Yes. Send yours and we will sign it before you share systems, data or credentials, or use our short mutual NDA — happy to email it on request. Either way your material stays confidential and is never used as a portfolio piece without your written sign-off.
Who owns the code?
You do. It goes into your repository, under your account, including the review engine. There is no platform to stay subscribed to and nothing stops working if you stop working with us.
Can I see client references?
Not yet — this offer is new and we would rather say so than invent them. What we can show you is three multi-agent systems we built for our own work, each with a review engine that can fail it, and the source of the gates. On a call we will walk through one in detail, including what it caught.

Start a project

Tell us what's eating your week.

We'll get back within one business day on whether it's a fit, what the pass/fail criteria would look like, and which tier it lands in. Or book a 15-min call.

What you share is kept confidential. NDA on request.

Prefer email? hello@byitl.com

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