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See what was asked.
Inspect what came back.
Choose your next move.
DoneHat connects buyer questions to saved answers and cited sources, so your team can review a useful fix and recheck what changed.
One lifetime attempt. No card required.
Free plan. Paid plans from $19 a month. No card to start.
Verified business email and completed business profile required. Includes up to $2 of lifetime processing per free account across setup and the snapshot, within shared service limits.
A stopped attempt can use the trial. Completion is not guaranteed.
The allowance is processing capacity, not cash or a billing credit. Agent drafts and proof checks depend on your plan and are not included in the free snapshot.
From one question to a clear next step
Illustrative walkthroughNo live scan or customer results
Every step keeps its context. Every result keeps its limits.
Start with the question your buyer needs answered. Keep the same wording when you recheck, so the later comparison has useful context.
Illustrative text · not an observed AI response
“Check the product’s integrations guide for the tools it supports.”
A saved answer and citation show what was returned. They do not prove why an AI included or omitted a brand.
Use a suggested change as a starting point. Your team checks the facts and supporting sources before approving anything for publication.
After approval, retain the published page and publication evidence before requesting a comparable recheck. Approval alone is not publication.
This example has no published change or receipt.
After a reviewed change is published, repeat the same question. Until comparable evidence exists, the result stays unmeasured.
Unchanged and inconclusive are valid results. An answer change alone does not establish what caused it.
A question. Its evidence. A reviewed next step.
This illustrates the wider DoneHat workflow. Agent drafts and proof checks depend on your plan and are not included in the free snapshot.
Why we built DoneHat
When an AI answer describes the options, a good business can be missing, misunderstood or overshadowed by a better-documented competitor. A traffic dashboard alone cannot show you that answer.
We built DoneHat to connect that hidden answer to work a small team can actually finish: evidence, a focused fix, and a careful recheck.
Start with buyer questions. Inspect what the sampled answers say, which sources they cite, and where your business is missing or confused with another.
Turn an observed gap into a focused task: clarify a page, add verifiable product facts, or answer a question buyers cannot resolve.
Use a grounded draft to save time. Your team checks the facts and decides what to publish, then records the changed page and date.
Repeat comparable questions with the same recorded model. Keep the answers, source changes and uncertainty visible, including an inconclusive result.
Answer-first summary
DoneHat is an AI visibility monitoring and remediation platform for B2B software brands. It checks buyer-intent questions across configured AI and search answer sources, then shows whether your brand is mentioned, cited, accurately described, or displaced by competitors.
The workflow is built for SEO, GEO, AEO, and product marketing teams: inspect the answer, review a supported change, retain publication evidence, and rerun the same questions to compare results. An answer change alone does not establish its cause.
Mention rate, answer position, competitor dominance, cited sources, factual accuracy, and confidence range.
Missing mentions, weak comparison pages, uncited claims, stale product facts, thin FAQs, and unclear entity signals.
Rerun the same buyer questions after publishing and compare improved, unchanged, regressed, or inconclusive answers.
DoneHat is built for AI visibility work, not generic model hosting, chatbot building, or legacy rank tracking.
Who uses DoneHat
AI visibility is not only a marketing metric. It touches growth, content strategy, product messaging, competitive positioning, customer trust, and executive reporting. DoneHat turns those scattered questions into one operating workflow: monitor the answer, diagnose the gap, ship the fix, verify the change.
Extend SEO from rank tracking into answer-engine visibility. Monitor buyer questions, cited sources, competitor mentions, and suggested page-level changes to review.
Package AI visibility as a managed service. Run separate client accounts, assign fix tasks, export client-ready reports, and compare answers after reviewed changes.
Find out whether AI engines understand your category, your positioning, and your proof points before buyers make a shortlist without ever visiting your site.
What DoneHat measures
Search rankings tell you where a page appears. AI answers tell buyers what to believe. DoneHat measures the four things that matter when AI engines become the first page of research: whether you appear, what sources support the answer, whether the claims are accurate, and which fixes can change the outcome.
Read the workflowWhich buyer questions mention your brand, where you appear in the answer, whether you are framed as a primary recommendation, and how consistent that visibility is across platforms.
Which owned pages, competitor pages, review sites, documentation, or third-party sources AI engines use when answering your category's highest-intent questions.
Whether AI engines state your pricing, features, integrations, target customer, and differentiators correctly, or repeat outdated or competitor-favorable claims.
The concrete fixes that can improve your answer presence: page updates, structured data, FAQ sections, comparison content, entity briefs, and repeat proof checks.
From evidence to action
A score is the starting point. Use the report to choose one change, review it with your team, and check what happened next.
Read the sampled question, answer, and citations before deciding what needs attention.
Turn the evidence into a draft or task. Check every claim before publishing to your site.
Track what you changed and compare the same questions later. Unchanged and inconclusive results stay visible.
How it works
Paste your website. DoneHat identifies buyer-intent questions relevant to your category.
We check buyer questions across the AI and search answer sources enabled for your plan and brand account.
Use the evidence to choose one fix, repeat the same questions, and verify whether the answer changed.
Capabilities
Track your brand with ChatGPT-first observations now, then add extra answer sources only when they are configured and commercially justified.
See which competitors appear in the sampled answers and inspect the cited sources.
Confidence ranges and sample limits make the score harder to overread.
Get suggested comparison, FAQ, schema, and source fixes tied to the sampled evidence.
No generated fix is treated as truth until it is reviewed against your brand facts.
Repeat the same questions after fixes to see measurable before/after results.
Enter your website, then sign in and complete the business trial requirements.
Pricing
One trial snapshot attempt with up to 6 sampled questions and 3 answer attempts per question, within the trial processing allowance. Includes answer evidence and verified gaps. Business-email verification and business details are required.
Run snapshotA reviewed proof run for solo founders: 25 buyer questions, one fix brief, and one rerun.
Get founder proofWeekly evidence for one small brand with 25 buyer questions and unsupported claims suppressed.
Start SoloWeekly reruns, two fix briefs, and proof checks for a small team working one priority brand.
Start ScalerThree client brands, 100 buyer questions, and client-ready summaries for early agency packaging.
Start agency liteLaunch pricing is intentionally capped for founders, small SMEs, and small agencies. Custom managed work is scoped separately.
FAQ
Straight answers about how DoneHat measures answer visibility, protects evidence quality, and turns supported findings into reviewed work.
Need a specific answer?
Yes. Start with your website, a clear description of your offer and buyer questions that do not name your brand. DoneHat records a starting sample, distinguishes zero mentions from failed checks, and helps you review supported fixes. Competitors and analytics connections are optional. Publish a reviewed change and repeat comparable questions; improved visibility is not guaranteed.
Start with a qualified trial snapshot, then choose a plan for monitoring over time.
Sign in, verify a business email and add business details before your one-time trial snapshot.