Enterpret is a customer intelligence platform that connects support, sales and market signals into structured context that teams and AI workflows can use. An adaptive taxonomy organizes feedback into themes that evolve with the product, a context graph links each signal to the feature, segment, lifecycle stage and business outcome behind it, and dashboards quantify the results. Teams can ask questions of their data, trigger actions through workflow integrations, and expose the same knowledge to AI tools through an MCP server.
Enterpret is built for product managers, CX leaders, support operations and sales teams at fast-moving companies that already collect large volumes of feedback. Product teams use it to decide what to fix or build next, support teams to find repeat contact drivers, and revenue teams to understand what blocks high-value deals. Customer stories on its materials include Canva, Notion, Apollo.io, Bitvavo, Descript and Feeld. Teams that want to build their own AI workflows on top of customer understanding can use the structured layer instead of starting from raw text.
Typical questions include which patterns appear before churn, what to fix first for the highest-value users, and whether an onboarding change improved retention. A product team can track ticket volume and retention after a release to confirm a decision worked, while a support team can find why customers contact them repeatedly about one issue. Sales leaders can review deal-level themes, and engineers can connect Slack, Jira, Linear or Salesforce so insights trigger work where teams already operate. AI agents can read the same context through the MCP server for automated resolutions and follow-ups.
