Mitzu

The company offers an agentic product analytics platform that runs on a data warehouse and supports plain-language queries for funnels, retention, and cohorts without SQL or data copies.

The company offers an AI analytics agent that provides answers with verified SQL on a warehouse, aiming to reduce reporting backlog and speed product and growth decisions.

Run AI analytics for BigQuery with natural-language questions, verified SQL, and zero-copy execution. Mitzu helps teams answer product and growth questions faster on first-party data.

Run AI analytics for Snowflake directly on first-party data. Mitzu translates natural-language questions into verified SQL so product and GTM teams can move faster without losing governance.

The page discusses how Cloud, Private, and BYOC deployments affect data operations and analytics scaling with Mitzu.

Insights on agentic analytics, AI analyst assistants, and the future of data-driven teams — from the Mitzu team.

CLICKnCRUISE uses Mitzu for product analytics focused on customer retention, revenue attribution, and business growth.

Data Mesh vs Data Fabric comparison with features, pricing, data architecture, and which analytics stack each option fits best.

Amplitude pricing in 2026: Free covers 2M events a month, Plus starts at $0 and scales to 70M, and Growth and Enterprise are custom event-based deals.

Mixpanel pricing in 2026: Free covers 1M events a month, Growth starts at $0 and scales to 20M, and Enterprise is a custom annual contract quoted by sales.

Mitzu offers Analyst, Team, and Enterprise plans, each with unlimited events and no per-event pricing. A 14-day free trial is available without a credit card.

The page compares Mitzu with analytics tools.

The page compares Mitzu and Amplitude, highlighting semantic-layer grounding, reviewable SQL, and trusted data as ways to reduce hallucinated answers.

The unsampled alternative to GA4. Why product teams prefer warehouse-native analytics for accuracy, unlimited retention, and B2B account tracking.

The page compares Mitzu and Looker Studio for product and marketing analytics, including warehouse-native capabilities.

Growth at Mitzu. Expert in data engineering and product analytics.

Co-founder and CEO of Mitzu. Passionate about product analytics and helping companies make data-driven decisions.

Trusted agentic analytics for modern engineering teams. Semantic-layer grounding, warehouse-native metric alignment, and reviewable SQL on trusted data.

Empower product managers with trusted agentic analytics. Use semantic-layer grounded metrics to measure feature adoption, retention, and journeys without SQL.

Mitzu helps teams answer business questions on their own data warehouse—with an analytics agent, transparent SQL, and no copying data to third parties.

The page presents an AI analyst assistant in Slack that answers data questions live.

Ask funnel, retention, and cohort questions in plain language. Mitzu auto-builds a governed semantic layer and answers with deterministic, reviewable SQL.

Mitzu's privacy policy describes how it collects, uses, and protects data across its analytics products and website.

Mitzu says its warehouse-native analytics keeps data within the user's infrastructure and uses a zero-raw-data-exposure architecture.

Mitzu's legal terms cover use of its warehouse-native analytics platform, website, and related services.

GitHubRepository owner

István Mészáros builds a warehouse-native analytics layer that merges web and product analytics using a zero-copy architecture. It lets teams define metrics once and query them directly, avoiding syncs across five tools that may use inconsistent definitions of terms such as “active user.” Teams can review SQL together, clean up the logic, and move faster.

Jul 2025 · Humans of MartechNews article