ProductTwin
Digital Authority for product

AI can read your product data. Does it know what “adopted” means?

Connecting ChatGPT or Claude to product analytics, Jira and CRM gives AI access to events and fields, not the eligible users, target segment, activation definition or customer identity.

A failing product bet can therefore look healthy and consume another quarter of roadmap investment before anyone sees the problem.

MCP connects AI to your product apps. ProductTwin applies your terms, metrics, rules and goals before AI answers.

How many accounts adopted the feature?
AI + MCP Access without business meaning 31% adoption All accounts · inferred from connected events
  • Every account included in the denominator
  • A feature event treated as successful adoption
  • Workspaces counted as separate customers
Plausible answer Inferred meaning
ProductTwin Access with business meaning 11% in the target segment 45 eligible accounts · Goal: 30% by week six
  • Only the approved enterprise segment included
  • Adoption requires the configuration milestone
  • Workspaces resolved to contracted accounts
Governed answer Your approved definitions
Intervene now

Unblock the eligible accounts that stalled before the configuration milestone, ahead of week six.

Reads fromMixpanel · Amplitude · Jira · Salesforce · and 750 more

Before you fund the next quarter, know whether the product bet is working.

ProductTwin continuously tracks each product bet against its goal, target segment and adoption definition. When the evidence moves, it shows what changed, why the outcome is at risk and where intervention is still possible.

ProductTwin home screen flagging the product goals that need attention
Raise an alert
ProductTwin explaining what changed and why
Explain why
ProductTwin proposing a plan and asking for approval
Propose an action

ProductTwin prepares the evidence before the decision. Your team decides what to build, fix or stop.

Javier Corral Jr.

Javier Corral Jr.

Global VP Product Strategy & Sales, Netcore Unbxd

Watch the feedback →
The promise of AI is speed, but speed means nothing if you can’t trust the answer. HelloTwin gives me fast answers that I can trust, so I can focus on strategy instead of chasing numbers. That’s how we move from managing agents to managing outcomes.

Better together

Product outcomes don’t live in product analytics.Every function can change whether the bet pays off.

Engineering shows what shipped. Sales shows customer commitments and segment demand. Success shows adoption and retention. Finance confirms the revenue and margin at stake. Together, the Twins create one governed view of every product bet.

ProductTwin One governed view of product goals, adoption and business impact
EngineeringTwinDelivery, defects and dependencies
SalesTwinCustomer commitments, segment demand and pipeline
SuccessTwinAdoption, retention and customer risk
FinanceTwinRevenue, margin and investment
One Semantic Digital Twin Same users · Same accounts · Same segments · Same terms · Same metrics · Same rules · Goals that roll up

A quarter of roadmap is too much to spend on an inferred number. Start with the bet you are least sure about.