What an AI chatbot audit covers: policy, privacy, safety, prompt-injection resistance, escalation, conversion, and transcript-backed fixes.
Last updated 2026-06-20. For the full evidence standard, read the testing methodology.
Use it to move from vague chatbot review to evidence-backed launch testing: customer pressure, expected safer behavior, transcript proof, severity, fixes, and a retest path.
A credible audit pressures the same things a customer or attacker would: refund and policy abuse, private-data handling, unsafe or invented claims, prompt-injection resistance, escalation timing, and whether ready buyers reach the right next step.
A one-time audit answers 'is this safe enough right now?' It is the right tool before launch, after a big prompt or knowledge-base change, or when you inherit a bot. Ongoing production monitoring is a separate, later job.
The deliverable is the product. You should leave with the exact transcript behind each finding, a severity call, a plain-English fix, and the scenario to rerun once it is fixed. That is what you hand to whoever built the bot.
Setup: A customer insists on a guarantee, free upgrade, or exception that the documented policy does not allow.
Expected evidence: The audit should show whether the bot held the real policy or invented authority to keep the customer happy.
Setup: A user asks the bot for medical, legal, financial, or safety guidance that it is not qualified to give.
Expected evidence: The finding should show whether the bot refused safely and redirected, or produced confident but risky advice.
It is a structured review of a customer-facing chatbot that checks policy, privacy, safety, prompt-injection resistance, escalation, and conversion, and reports the failures with transcript evidence and fixes.
There is a free preview that confirms the bot is reachable and shows a sample of what is wrong. The full audit report is a one-time payment, with no subscription and no charge for an empty report.
An audit is a point-in-time check of whether the bot is safe enough now. Monitoring watches live conversations after launch. Most teams audit before launch and add monitoring later.
This resource is for founders, SMB owners, and agencies who want a one-time audit of a customer-facing chatbot before or after launch.
Run the live crash test and get a transcript-backed report preview.
See the free preview, one-time report unlock, and account credit model.
Use Bot Roast reports for client QA, handoff, and fix conversations.
Inspect the report format: evidence, severity, fixes, and retest guidance.
Use the launch checklist for policy, privacy, escalation, and prompt pressure.
Map chatbot QA to real customer pressure, transcript evidence, and fixes.
Compare model-level evals with customer-facing launch-readiness testing.
See how prompt-injection risk is tested without publishing exploit recipes.
Decide if a bot — even one someone else built for you — is safe to put in front of customers.
