See what AI is telling your customers about your products.
Your customers are asking AI tools and chatbots questions about your products every day. The answers they get are often wrong, incomplete, or out of date. We test those answers, document the problems, and give your QA, regulatory, and product teams something they can actually work from.
Independent evidence packages built for safety-critical product environments.
Evidence-based
Findings written for QA, RA, and PMS review workflows.
Built for regulated, safety-critical product environments
The problem
Customers are asking AI. The answers may not match your approved product information.
Clinicians, patients, distributors, sales reps, and your own support team all use AI tools when they need a quick answer about a product. Those answers are often incomplete or out of date. Sometimes they contradict your approved labeling, IFU, warnings, or claims. You usually find out when a customer asks why.
Wrong product claims
AI assistants describe your devices confidently and get the details wrong.
Old IFU content showing up
Superseded versions of instructions for use appear in answers and search summaries.
Unsafe usage suggestions
Reuse, off-label, or misuse ideas that contradict your approved labeling.
Wrong region, wrong claim
US claims or availability surface in markets where your product is not cleared.
Distributor chatbot errors
Third-party bots represent your brand with omissions or incorrect specs.
Warnings that disappear
Safety statements get dropped, paraphrased, or softened in generative answers.
Wrong sources surfacing
AI tools pull from low-quality third-party pages instead of your approved materials.
Defect taxonomy
The kinds of AI answer defects we look for.
Findings are grouped into four consistent categories so QA, RA, PMS, and product teams can review, prioritize, and trend issues over time.
Safety and clinical risk
- Unsafe use instructions
- Missing warnings or contraindications
- Off-label implications
Regulatory and claim compliance
- Incorrect product claims
- Outdated IFU references
- Regional availability errors
Source quality and information errors
- Hallucinated specifications
- Translation drift
Distributor, regional, and chatbot issues
- Distributor chatbot omissions
- Poor escalation behavior
Who it's for
For the people who own product information risk.
If a wrong answer about your product creates a safety, regulatory, support, or brand problem for your company, this service is built for you.
Outcomes
From scattered AI outputs to findings you can act on.
Each AI answer that looks risky becomes a documented finding. It carries a severity rating, the rationale behind it, and a recommended next step. Your team can review it the same way you review any other quality input.
See how it works- Catch risky answers early, before they spread
- Protect customer safety and product trust
- Feed structured inputs into your PMS process
- Raise the quality of chatbot and AI responses
- Prioritize content gaps by actual risk
- Give QA and RA real evidence, not loose screenshots
What you receive
A structured evidence package, not a folder of screenshots.
Every engagement produces a single, organized package your team can review, prioritize, and route to the right owner.
Tested prompt library
Structured prompts mapped to your products, claims, and risk categories.
AI source and chatbot coverage summary
The public generative engines, AI search overviews, and bots covered in scope.
Captured outputs and screenshots
Reproducible evidence of the answers we observed.
Finding log with severity and rationale
Each finding rated and explained so you can review and prioritize.
IFU, labeling, or claim comparison
Where applicable, observed answers are compared against the materials you provide.
Regional and language flags
Answers flagged where availability, clearance, or claims do not fit the region.
Recommended corrective actions
Practical content, channel, or escalation steps for each finding.
Executive summary and trend reporting
A clear leadership view of risk and how it moves between cycles.
Services
Services built around how regulated teams already work.
Core monitoring services
AI Answer Monitoring
Ongoing testing of public AI tools and generative engines covering product questions, safety information, claims, warnings, and instructions for use.
Chatbot Answer Testing
Independent testing of company, distributor, ecommerce, and customer service bots. We check accuracy, consistency, safety information, and how the bot escalates.
AI Answer Intelligence for Post-Market Surveillance
Recurring reports on AI-generated product answers, repeating question themes, and risk-rated observations. Useful as inputs to PMS review, complaint triage, CAPA discussion, and content updates.
Specialized and add-on services
Regional and Translation Review
We test whether answers shift by country, language, or regulatory context, and flag anything that does not fit the local market.
Source Content Gap Review
We identify the missing, unclear, or outdated source content that tends to produce weak AI answers.
Bot Validation Support
Structured test scripts, acceptance criteria, defect logs, and evidence packages for internal customer-service AI bot validation or release readiness.
Reports support internal review and decision-making. They do not replace required complaint handling, PMS, regulatory, or quality system processes.
Our process
A repeatable program that produces QA-grade evidence.
Four steps. Each one builds on the last, from scope to traceable finding.
- 01
Define scope
We agree on product families, regions, AI tools, chatbot channels, and the question categories that matter most for risk.
- 02
Test real-world prompts
We run a structured set of prompts drawn from real customer, clinician, distributor, and support situations.
- 03
Classify and prioritize
Each answer defect is rated for severity, likelihood, safety relevance, regulatory impact, and business risk.
- 04
Report and improve
You get the report with screenshots, findings, ratings, recommended actions, and trend tracking across cycles.
What makes us different
Visibility is not the same as assurance.
Generic SEO and GEO agencies help you get mentioned. We look at the answer itself and ask whether it is accurate, safe, current, and useful as evidence.
- Visibility rankingAccuracy, safety, and product information risk
- Marketing screenshotsEvidence packages QA and RA can actually use
- Generic contentAlignment with IFU, labeling, and approved claims
- Volume metricsRisk-based prioritization
- Marketing reportingInputs your PMS process can review
- Single-region focusRegional and language context
- Brand mentionsChatbot and AI answer testing
Illustrative examples only
What an AI Answer Audit can uncover.
Every finding lists the prompt tested, the channel where the answer appeared, the issue we observed, a risk rating, and a recommended action. The rows below are illustrative.
| Prompt tested | Channel tested | Observed issue | Risk level | Recommended action |
|---|---|---|---|---|
| Can I reuse this disposable device? | Public AI Assistant | Answer implied reuse was acceptable despite single-use labeling. | High | Update source content and monitor recurring prompts |
| What warnings apply to this product? | Distributor Chatbot | Bot omitted a key contraindication listed in approved labeling. | High | Escalate to chatbot owner and revise knowledge base |
| Is this product available in Canada? | Search AI Overview | Answer referenced US availability only; no regional clarification. | Medium | Improve regional product page structure |
| How do I clean the reusable handle? | Public AI Assistant | Cleaning steps summarized an outdated IFU revision. | Medium | Refresh public IFU and structured data |
Illustrative examples. Actual findings depend on engagement scope, products tested, and AI sources covered.
Packages
Engagements sized to your program.
Three structured tiers and a set of focused add-ons. Every engagement is scoped to your product portfolio and regulatory context.
Starter AI Answer Audit
A focused review of one product family across selected prompts and major AI sources. A practical way to see where the real risks sit before committing to ongoing monitoring.
Scoped engagement
- One product family in scope
- Selected prompts across key risk categories
- Major public AI answer sources
- Risk-rated findings report
Monthly Monitoring Retainer
Ongoing AI answer monitoring for teams that need to keep track of risk across product families, channels, and recurring customer questions.
Monthly engagement
- Recurring prompt testing across cycles
- Trend, risk score, and movement reports
- Regional and chatbot spot checks
- Recommended content and escalation actions
- Quarterly executive summary
Regulated Intelligence Program
For mature QA, RA, PMS, or support teams running at scale across regions and channels.
Custom quote
- Multi-region monitoring
- Chatbot testing and validation
- PMS-aligned reporting
- Source content review
- Executive summaries
Add-ons
Scope depends on your product families, regions, languages, channels, source materials, and internal review needs.
Fix risky AI answers before they reach more customers.
Request a focused AI Answer Audit. You will receive a risk-rated report covering accuracy, safety, regional fit, chatbot behavior, and content gaps.
About
Visibility is easy. Confidence in the answer is the hard part.
Answer Assurance was built for companies that need more than tracking where they appear in AI tools. They need confidence that the answers being produced are accurate, safe, current, and consistent with what regulated products require.
We combine independent AI answer testing with the structured thinking quality and regulatory teams already rely on: risk-based assessment, traceable evidence, and remediation recommendations that fit how your team already works.
- AI answer testing
- Quality and regulatory thinking
- Risk-based assessment
- Structured reporting
- Practical remediation recommendations
FAQ
Frequently asked questions.
Have something specific to your portfolio? We are happy to walk through it.
hello@answerassurance.comWhat is AI answer monitoring?
It is the practice of testing what AI tools, search assistants, and chatbots actually say when someone asks about your products. That includes claims, safety information, instructions for use, and regional availability.
Is this the same as SEO or GEO?
No. SEO and GEO are about visibility and ranking. We focus on whether the answer itself is accurate, safe, and current. Two different problems.
What AI tools do you test?
Major public generative engines, AI search overviews, AI chat assistants, and the customer-facing, distributor, or ecommerce chatbots that fall within your engagement scope.
Can you test our customer service chatbot?
Yes. We provide independent test scripts, defect logs, and evidence packages that fit into release readiness or validation activities.
Can this support post-market surveillance?
Our reports give your team structured inputs that may inform PMS, complaint triage, and CAPA discussions. They do not replace required complaint handling, PMS, regulatory, or quality system processes.
Do you review answers against our IFU or approved labeling?
Yes. You provide the approved materials and we assess observed answers against them, with clear traceability in the finding log.
Can you monitor different countries or languages?
Yes. Regional and translation review is a core capability and is scoped per country, language, or regulatory context.
What do reports include?
The prompts we tested, the AI channels we covered, the answers observed, screenshots, risk classifications, recommended actions, and trend tracking across cycles.