How is Vantage different from ChatGPT or Claude?

ChatGPT and Claude write you a document. Vantage keeps the document, prototype, tickets and roadmap connected to the feedback and decisions behind them, and tells you when one of them changes. You can also bring your Vantage context into Claude or ChatGPT, so you don’t have to choose.

Do I have to move off Notion or Linear?

No. Keep the tools you use and connect them to Vantage. Tickets push to Linear with two-way sync, and you approve every change that comes back.

What can I do in the first ten minutes?

Paste customer feedback or describe a problem, and get a PRD with every requirement linked to its source. You can try the demo on this page without signing up. Connect your tools whenever you’re ready.

I own several projects. What does Vantage do across them?

It briefs you every morning on what needs your call, catches specs that contradict each other, and flags anything that went stale after a decision changed. It works for a single project and earns its keep at two or more.

What if the AI gets something wrong?

Nothing updates silently. Every requirement cites the quote, call or metric behind it, and every change arrives as a diff you accept or reject before it touches your docs, tickets or Linear.

Can I use Vantage from Claude or ChatGPT?

Yes. Connect Vantage’s MCP server to Claude, add the GPT Action in ChatGPT, or use an API key. Then ask about your projects, search your specs, or create tickets from wherever you work.

Start on your own for free. When teammates join, they work from the same context, with admin, editor and viewer roles and private drafts that stay invite-only until you publish.

What does fair use mean on the unlimited features?

Unlimited features are meant for real day-to-day work by one person: up to 50 questions a day on Pro and Business, and on Business up to 10 PRDs, journeys or ticket batches a day. Very few people get close. If your team regularly needs more, talk to us.

Your data is encrypted in transit, and we never train on it. The AI providers we use are contractually barred from training on it too. You can disconnect any integration or delete your account at any time. We’re pursuing SOC 2 Type II.

How much does it cost?

Vantage is free to start with 300 credits and no credit card. Projects are unlimited on every plan, and AI work like generating a PRD or a ticket batch uses credits. Pro is $19 per seat a month billed annually ($25 monthly) with 1,500 credits a month, unlimited questions and prototypes. Business adds a shared team workspace and 4,000 credits per seat a month.

Is this an automatic Amplitude audit?

No. It is a review process using saved analyses and documented data semantics.

What if one check fails?

Pause the consequential interpretation, fix or qualify the measurement and preserve the original evidence.

What should the final note contain?

The observation, query definition, confidence limits, likely explanations and the specific next action.

Product workflows2026-10-282 min read

Audit an Amplitude Metric Before a Decision

Before acting on a metric, verify that it measures the intended outcome for the intended population and period. This is a manual analysis checklist, not a native certification that a chart is decision-ready.

Before you start: Have the saved chart, underlying definitions and one known user journey. Identify the decision and the harm of drawing a wrong conclusion.

Worked example: A reported activation drop could reflect a release, a missing event property or an incomplete cohort. The checklist should establish trust before the team prioritizes an onboarding redesign.

Step-by-step guide

State the decision

Write what action the metric could change. Define the outcome and counting unit before reviewing the visualization.

Verify event meaning

Check the trigger, success condition and recent instrumentation changes. Compare a known journey with the report.

Inspect identity and population

Review eligibility, internal-user exclusions and the relevant identity contract. Confirm the denominator reflects real opportunity.

Check time and maturity

Align date ranges, time windows and cohort age. Identify incomplete data or periods with different capture coverage.

Reproduce the result

Open the saved analysis and verify filters and segmentation. Record enough query context for a colleague to repeat the check.

Write a qualified conclusion

Separate the observation from the explanation. Record uncertainty, a next investigation and the owner of any data-quality fix.

Common mistakes

Chart title trusted alone

A label can conceal a different query.

Time windows ignored

Unequal observation can create false deterioration.

Association becomes cause

A valid metric still does not prove the proposed explanation.

Tips

Keep a known journey as a sanity check.

Record capture changes before discussing product impact.

Ask a second person to reproduce the query.

Sources and verification

Based on product documentation checked on 2026-10-24. This is a documentation-based guide, not a hands-on benchmark. Features and availability can change.