Harvest Analytics raises $21M to launch product analytics with model-powered insight generation

Tech · 5 min read

Harvest's platform combines event-level telemetry with generative insight assistants that propose hypotheses and relevant cohorts for experimentation. The Series A will be used to improve causal inference capabilities and add deeper mobile SDK features.

The product auto-annotates funnels with potential drivers and suggests experiment designs ranked by expected impact. Harvest positions this as a way to reduce analyst bottlenecks and democratize data-driven discovery for product teams.

Designers and PMs testing the system liked the proactive suggestions but emphasized the need for clear uncertainty estimates and guardrails to prevent over-reliance on automated hypotheses. Harvest added explainability modules showing the data slices that led to each suggestion.

The company plans enterprise-grade governance, role-based views, and integrations with experimentation platforms so suggested hypotheses can be A/B tested with minimal friction.