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Hands-on testing for AI products.

What does your AI product do when a stranger sets it up?

I test AI tools the way a new customer meets them: a blank workspace, your main scenario, and a network capture running the whole time. You get a private report of what broke, where it broke, and what your product does that your docs and privacy policy do not mention.

Hosts contacted by the customer-facing chat pageSample test, October 15, 2026
HostFirst seenCarriesIn the privacy policy
vendor chat hostchat page, widgetyes
vendor static hostwidget assetsnot named
api gateway, different domainmessages, transfer-to-human callnot named
icon font CDN, other jurisdictionicon fontnot named
analytics beacon, large CDN providerpage analyticsnot named
Widget cookie and storage keys carry the name of a different customer-service platform.asked, not asserted
Five AI products tested hands-on. Each finding comes with a severity, reproduction steps, a timestamp and a screenshot. Synthetic data only. Findings stay with the client.
Method

Two weeks on one scenario,
from a blank account to a retest.

The full method →

You tell me the product and the one scenario your customers run most. I sign up like a stranger, set it up from the docs alone, run the scenario from a clean state until it breaks or holds, and keep a network capture running throughout. About two weeks later you have a findings report, a short list of questions a careful buyer would ask you, and one retest round for whatever you fix.

Day 0Scope

One product, one scenario, agreed in writing before I start.

Days 1 to 2Setup

Blank workspace, docs only. Steps the docs skip get written down.

Days 3 to 8Run

Clean state each time, network capture on, a timestamp on each step.

Days 9 to 10Report

Severity, reproduction steps, screenshots, questions for your team. Then a retest.

9:01 to 10:10 PM

Seventy minutes on a public trial.

The test behind the sample report: one unpaid 70-minute session on a vendor’s public trial. A paid audit runs the same method over about two weeks, with many more runs of your scenario from a clean state.

  • Trial account created. Blank workspace, docs open in the next tab.
  • Knowledge base built from the vendor’s own FAQ format.
  • First customer question goes unanswered: no AI reply, no handoff, no “please wait”.F1
  • The same question answered once the FAQ was re-uploaded as a document.
  • Human step changed to accept chats the AI already holds. Nothing in the builder suggested it.
  • Handoff works. The AI transfers without waiting for the customer’s yes.F4
  • A second automation placed above the default stops all routing.F1b
  • Talk-to-a-human button finally works, as a second trigger inside the default automation.F2
  • Settings checked for the consent option the privacy policy promises. There is none.F3
  • Session closed. 8 findings, 25 screenshots, 5 hosts in the capture.
Scope sheet

For makers about to launch, reprice, or roll out.

Compare the two tests →

What I test

  • Setup from a blank workspace, using only your docs.
  • Your main user scenario, run end to end from a clean state until it breaks or holds.
  • Which hosts the product contacts, compared with what your privacy policy and docs claim.
  • Limits, caps and what the trial really includes.

What you get

  • A written findings report. Each issue has a severity, reproduction steps, timestamps and screenshots.
  • A short list of the questions a careful buyer or security reviewer would ask your team.
  • One retest round for the items you fix, inside an agreed window.

Terms

  • Fixed price, quoted up front.
  • Half on start, half on delivery of the report.
  • Findings are private to you.
  • Synthetic data only.
Price: fixed, quoted up front for your product and scenario.
Rate card
EngagementForWhat happensYou get
Pre-launch auditAI tool makersBlank workspace, one scenario, network capture.The findings report, the vendor questions and one retest.
Buyer’s testTeams choosing a toolYour scenario, run on the product you are about to buy, before you sign.A go or no-go memo with the evidence.

Each pre-launch audit includes one retest round for the items you fix. Further rounds are quoted separately.

Real output

What a finding looks like.

Read the full sample →
High

F1. Failed routing leaves the customer in silence, with no warning to the admin

What happens. Five separate configuration states left the customer with no reply, no “please wait” and no handoff (9:16 PM, 9:18 PM, 9:26 PM, 9:30 PM, 9:51 PM).

Cause, confirmed. The AI step’s fallback does nothing if the next human step only accepts unassigned chats, which is the default. Adding the status fixed it (changed 9:37 PM, confirmed 9:38 PM).

Reproduce.
  1. Insert an AI agent step before the default human step.
  2. Leave the human step on its default filter.
  3. Ask something the knowledge base does not cover.
Expected: handoff. Actual: silence.
Evidence: screenshots 10 to 13 and 19. Timeline 9:16 PM to 9:31 PM.
House rules
  1. Separate from OpenSourcesAI.Paying for an audit buys no coverage, placement or ranking on opensourcesai.com. Before a buyer hires me to test a vendor’s product, I tell them about any paid work for that vendor.
  2. Findings come with evidence.Each one has a timestamp and a screenshot. Anything I could not verify is marked as not verified.
  3. Your customers’ data stays out.I work with a made-up business and test accounts. Real customer data does not go into the product during an audit.
  4. One agreed scenario.Keeping to one scenario lets your team rerun the same steps and compare the result.
  5. Fixed price.The number in the quote is what you pay. I do not bill by the hour or add charges partway through.
Track record

Found on real products.

How a line gets here →
ProductWhat I foundWhat happened next
Desktop privacy assistantThe “send original” option still sent the masked text to the model. The free tier failed on first use. The office add-on sent a 6,770-token prompt into a 4,096-token context.The developer confirmed all three and shipped a fix.
Agent security toolThe claimed runtime blocking did not fire. Traced to two causes in how it registered its hooks.The maker got exact commands, logs and a redacted config.
Local AI chat clientA wire-level host check found it bound to loopback only, and the binary unsigned.Reported to the maker.
Screen-recording toolAnalytics and crash reporting on by default, and it captured background browser tabs. Neither was in its README.Reported to the maker.
Hosted AI customer-support platformThe AI-to-human handoff needed four undocumented setup steps, and each misstep left customers in silence. The privacy policy promised an AI consent notice the product did not show.Report shared with the vendor. It is the basis of the sample report.
Questions

Before you ask for a quote.

More questions →
Is this a penetration test?
No. I test from a customer’s account and stay within what a customer can reach, so there are no exploit attempts, no source code review and no legal opinion. If you need a penetration test, hire a pen tester as well; the two cover different ground.
What do you need from us?
The product, the one scenario you care about most, and a trial or test account. If the trial is too short for the scenario, a test workspace with a longer clock.
How long does it take?
About two weeks from kickoff to report. A retest takes a few days. The clock starts when the scope is signed and the first half is paid.
Will you publish anything?
No. The findings are yours and stay private. If you agree in writing, one anonymized line can go on the track record page, without the product’s name, the vendor’s name or any other detail that would identify either.

Tell me the product and the scenario.

I reply with a fixed quote and dates.

Request a quote