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.

Can a release comparison prove impact?

Not by itself. Use a suitable randomized experiment or stronger evaluation design for causal claims.

What if there is no exposure event?

Use the best verified eligibility proxy and state its limits instead of claiming actual treatment.

How long should we observe?

Long enough for the chosen outcome, with equal observation opportunity across cohorts.

Product workflows2026-10-262 min read

Compare Release Cohorts in Amplitude

Define who could encounter the release and compare groups with equivalent observation time. A before/after cohort comparison is descriptive; it does not isolate causality when acquisition, seasonality or eligibility also changes.

Before you start: Have a release timeline, validated events and an exposure or eligibility marker. Confirm cohort availability under your plan.

Worked example: Compare new owners who could use the revised invite flow with a prior cohort at the same age. Do not include users who never received the release as treated participants.

Step-by-step guide

Define the release boundary

Record deployment, rollout stages and eligibility. A merge date is not proof that every user saw the feature.

Construct the cohorts

Use explicit entry periods and relevant exposure or property criteria. Keep the original cohort definitions available for review.

Align maturity

Give each group the same time to activate or return. Exclude incomplete observation from the comparison rather than treating it as failure.

Keep outcomes fixed

Use the same events, window, counting unit and exclusions. Document any instrumentation change that could alter the result.

Check composition

Compare major acquisition or role differences between groups. Inspect whether a mix change could explain the outcome.

State a bounded conclusion

Report association and limitations, then choose a follow-up test or investigation. Avoid assigning the entire change to the release.

Common mistakes

Deploy equals exposure

Rollouts can be partial. Check actual eligibility.

Unequal age

Recent cohorts have less time to succeed.

Before/after equals causal

Other changes can explain the difference.

Tips

Keep the rollout timeline beside cohort definitions.

Compare a stable segment as a sensitivity check.

Record instrumentation changes before interpreting lift.

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.