Mitzu

Agentic analytics that tells you why metrics moved—with full SQL visibility

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Added Jul 2026

mitzu.io

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What is Mitzu?

Mitzu is an agentic product analytics platform that diagnoses why key metrics move by running analyses directly in your data warehouse. It automatically creates a semantic layer from your warehouse schema, then uses deterministic SQL generation—not hallucinated queries—to answer complex product questions through funnels, cohorts, and retention analysis. Built for product teams, analysts, and data-driven companies who need trusted, explainable answers to hard analytical questions.

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Key Features of Mitzu

Impact Analysis for measuring feature and campaign effects
Deep Dive diagnostics across funnels and cohort breakdowns
Hypothesis Validation against real user behavior
Monitoring & Anomaly Detection with Slack/email alerts
Automatic Semantic Layer generation from warehouse schema
Deterministic SQL Engine ensuring consistent results
Zero SQL hallucinations with full query visibility
Supports Snowflake, BigQuery, Databricks, Redshift, ClickHouse
10-minute setup with no YAML configuration

Who Should Use Mitzu?

Diagnose why user churn increased

Understand funnel drop-offs

Investigate retention declines

Analyze activation stalls

Track cohort shrinkage

Monitor DAU spikes

Measure product release impact

Validate onboarding assumptions

Detect metric anomalies proactively

Mitzu: Pros & Cons

✓Pros

Automatic semantic layer—no weeks of YAML configuration
Full SQL visibility for every answer
Deterministic results—same question always produces same SQL and answer
No LLM hallucination of queries
Works directly in your existing data warehouse
Handles complex product analytics methodology (funnels, retention, cohorts)
Proactive monitoring surfaces insights before you ask
Quick setup in under 10 minutes

Frequently Asked Questions about Mitzu

What data warehouses does Mitzu support?

Mitzu works with Snowflake, BigQuery, Databricks, Redshift, and ClickHouse.

How long does setup take?

You can connect your data warehouse and create a semantic layer in under 10 minutes with no complex setup required.

Does Mitzu use SQL generated by an AI?

No. Mitzu uses a deterministic SQL engine where the agent assembles a specification and the engine generates SQL, ensuring consistent and verified queries with no hallucination.

Can I see the SQL behind Mitzu's answers?

Yes. Every answer includes full SQL visibility so analysts can verify the logic before sharing with stakeholders.

What types of analysis can Mitzu perform?

Mitzu can perform impact analysis, deep dives into metric movements, hypothesis validation, and continuous monitoring with anomaly detection.