Bagel AI

For project and product managers, the core challenge is cutting through noise to make evidence-backed decisions. Bagel AI replaces manual triage and subjective prioritization by creating a single, autonomous decision layer. It ingests every signal—from sales calls in Gong and CRM notes in Salesforce to support tickets in Zendesk and Slack threads—and uses a bespoke AI model to consolidate them. This process claims to reduce duplicated data by 85%. Crucially, Bagel AI quantifies the impact of every potential feature by tying it to GTM requests, deals, and ARR. A request isn't just a ticket; it's a revenue case. The platform then proposes the next product moves, ranked against your existing roadmap, ready for the next sprint. It closes the loop by measuring the impact of shipped features on adoption, revenue, and retention, citing results like a 15% churn reduction and a 23% increase in net new revenue. For teams using AI coding assistants like Cursor or Claude, Bagel AI provides the essential customer context, ensuring engineers build the right thing, faster.