For AI products that work “most of the time”

Find out exactly where your AI breaks, how often, and how badly.

Your AI works in demos and slips in production. We build 300+ tests, break it before your users do, and hand you a scorecard of every failure ranked by cost. Done for you, human-verified, in 7 business days.

7 business days from kickoff to report · first findings in 48 hours
eval /ɪˈval/ noun · informal shorthand for “evaluation”
1. Plain EnglishA real, repeatable test of whether your AI actually does its job — run over hundreds of realistic cases instead of the handful you try by hand.
2. Think of it asA health check with a scorecard: what your AI gets right, where it fails, how often, and what to fix first.

— Most AI products have never had one. That is the whole reason this company exists.

The problem/ 01

Hope is not a QA strategy.

Early AI products ship on vibes. The team tries the happy path by hand, someone pastes the good screenshots into Slack, and the actual failure rate is anyone’s guess. That is not a model problem, it is a measurement problem. There is no representative set of tests, no objective way to score right from wrong, and no one deliberately trying to break the AI before real users and real attackers do it for you. So the behavior stays hit and miss, every fix is a guess, and every demo is a coin flip.

Sound familiar?
✗The same question gets three different answers.
✗You don’t know your failure rate. Nobody does.
✗“Testing” means the founder trying the happy path by hand.
✗One viral screenshot of your AI saying something wrong keeps you up at night.
✗An enterprise prospect asked “how do you test this?” and you changed the subject.
✗You know you need real testing. You don’t have 6 to 8 engineer-weeks to build it.
The audit/ 02

A complete reliability check of your AI, run for you and handed over.

One engagement. Eight deliverables. A human checks every single score.

01

Failure Map

We learn your product, your users, and what a wrong answer actually costs you. Then we rank the ways it can fail by business damage, not by count, so you fix what hurts first.

02

The Test Set (300+ cases)

Over 300 realistic tests built for your product: normal requests, tricky edge cases, trick questions, off-topic bait, and multi-step conversations. You keep a copy. We hold a second set back so future re-tests stay honest and nobody can quietly “study for the exam.”

03

Human-Calibrated Scoring

Clear, objective rules for what counts as right or wrong. Where we use AI to help score at scale, we check it against human graders and publish how often they agree. Objectivity as a stat, not a claim.

04

100% Human-Verified Results

Trust anchor

A person reviews every scored result. No fully automated grades anywhere in your report. This is the trust anchor of the whole engagement.

05

Adversarial Red-Team

We attack your AI on purpose: attempts to jailbreak it, feed it hidden instructions, pull private data out of it, or bait it into biased answers. Better us than a stranger with a screenshot.

06

Reliability and Ops Panel

The same question asked 10 times, measured for how much the answers vary. How often it makes things up, with the receipts. Speed and cost per answer. This is where “hit and miss” becomes an actual number.

07

The Reliability Report

Your scorecard, a side-by-side against a leading off-the-shelf model, every failure with steps to reproduce it, and a fix list ranked by priority. Your investors can read the first two pages; your engineers can act on the rest.

08

Fix-Verification Re-Test

Within 90 days, after your team ships fixes, we re-run the held-back tests and prove what got better, what didn’t, and whether anything new broke.

Included bonuses

Eval Kit Handover

Your test set and scoring rules, documented, so your team can keep testing between engagements.

Findings Walkthrough

A live 90-minute session walking your engineers through every critical failure. Recorded, yours to keep.

The Reliability One-Pager

A shareable one-page summary written for your enterprise prospects and investors, not for engineers.

Pricing/ 03

One audit. One price.

The audit · fixed · delivered in 7 days
$4,995

The full stack: the failure map, the 300+ test set, human-calibrated scoring, a 100% human-verified run, the adversarial red-team, the reliability panel, the Reliability Report with fix roadmap, the fix-verification re-test, and all three bonuses.

The guarantee

If we don’t uncover at least 25 failure modes you didn’t already know about, you don’t pay.

What it’s worth
Failure Map$1,500
The Test Set (300+ cases)$3,500
Human-Calibrated Scoring$1,500
100% Human-Verified Run$2,500
Adversarial Red-Team$2,500
Reliability and Ops Panel$1,500
Reliability Report + roadmap$2,000
Fix-Verification Re-Test$1,500
AI Tokens for running Evals$1,000
Bonuses (all three)$1,500
Total value$19,000
Your investment$4,995
You save$14,005
Optional$3,000

Eval framework + code

The full runnable test harness we built for your product, handed over so your team can re-run the entire evaluation themselves, anytime.

Optional$5,000/mo

Fix Sprint retainer

Don’t want to fix it yourself? We implement the roadmap: prompt fixes, guardrails, retrieval improvements, re-checked against the held-back tests every month.

Extra jobs beyond the 5, and extra re-test cycles, are available as add-ons.

Net cost

One churned enterprise customer, one failed procurement review, or one viral failure screenshot costs more than this entire audit. $4,995 is less than one week of a senior engineer’s fully-loaded cost, and building this in-house takes that engineer 6 to 8 weeks. This ships in 7 business days, with a human verifying every score.

How it works · 7-day audit/ 04

From first call, to a report you can hand to your dev team in 7 days.

Fully done for you. Your team’s total time is about 3 hours: a kickoff, a quick mid-point check, and the findings walkthrough. All days below are business days.

Domain deep-dive Build & evaluation Report & walkthrough
Day 0 · Discovery call We scope your product and agree which jobs your AI does that we’ll test (up to 5). Book a discovery call →
Mon Tue Wed Thu Fri
1 Deep-dive

Failure map and severity ranking begin.

2 Deep-dive

Scoring-rule draft. First informal findings shared.

3 Build & eval

300+ tests built for your product.

4 Build & eval

Attacks run, reliability measured.

5 Build & eval

Every score verified by hand.

6 Report

Reliability Report delivered.

7 Walkthrough

Live walkthrough with your dev team. Fix roadmap agreed.

Delivered You ship the fixes. Then the held-back re-test proves them, below.
Within 90 days · Re-test After your fixes ship, we re-run the held-back tests and deliver a before-and-after report.

A “job” here means one distinct thing your AI does end to end. For a booking assistant, “book an appointment” is one job and “reschedule or cancel” is another. Up to 5 per audit.

The team/ 05

Your audit is run by Claude Certified Architects.

Every eval is written, run, and hand-verified by our team of Claude Certified Architects (CCA-F) — not a self-serve dashboard, and not a QA vendor who’s never watched an AI product fail in production. We’ve spent 15+ years shipping real software and the last 3 years building and running evals full-time. We know exactly how these systems break, because breaking them is the job.

The team behind theevalscompany — Claude Certified Architects
CCA-F certified The team behind theevalscompany · a Cogent Labs offering
CCA-F Claude Certified Architects

A certified architect on every single engagement, start to finish.

15+ yrs Engineering experience

Building and shipping production software across the team.

3 yrs Writing evals

Designing, running, and grading evals full-time, not as a side project.

The transformation/ 06

Before, and after.

Before
−Works in demos, misbehaves in production.
−QA is a founder pasting outputs into Slack.
−“How accurate is it?” gets a shrug and a guess.
−Every provider model update is a silent gamble.
After
+You know your failure rate per job, per severity.
+The worst failures are fixed, and proven fixed on tests you never saw.
+Procurement asks how you test; you hand them the one-pager.
+Same input, same answer. Finally.
Proof/ 07

See exactly what you’ll get, before you ever get on a call.

We built a complete sample engagement for a fictional voice assistant that books pet-grooming appointments. It’s the full Reliability Report a real client receives: the failure map, the test-set overview, the scoring rubric with agreement stats, the human-verified results, the red-team findings, the reliability panel, and the re-test delta. Read the whole thing and judge the quality for yourself.

Book a discovery call →
First client engagements underway · until then, the sample report is the proof
Reliability Report Human-verified
01 · failure map 02 · test-set overview 03 · scoring rubric · agreement stats 04 · human-verified results 05 · red-team findings 06 · reliability panel 07 · re-test delta
Fictional client · real format