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Mitzu
Agentic product analytics that runs on your data warehouse
Mitzu is an agentic product analytics platform that runs on your data warehouse — built to answer the why, not just the what. Ask complex questions like "why did week-2 retention drop?" and the Analytics Agent investigates across funnels, cohorts, and segments, returning a synthesised answer. No hallucinated SQL: a deterministic engine produces methodology-correct queries every time. Your data stays in Snowflake, BigQuery, Databricks, Redshift, or ClickHouse.
This is sick! Don't all of these warehouses have AI analysis built in? ie snowflake cortex? What advantage does Mitzu have over the in-house solutions?
I'm Istvan, founder of Mitzu. We built this because we kept watching the same frustrating loop happen:
A data analyst fields a Slack message: "Why did activation drop last week?" ➡️ Opens a notebook, writes three SQL queries, finds a partial answer, and posts it two hours later. ➡️ The PM asks a follow-up. ➡️ The cycle repeats.
The problem isn't the analyst. The problem is that answering diagnostic product questions (not just "What was DAU?" but "Why did week-2 retention drop in November?") requires two things that haven't lived together until now:
Access to all the data in your warehouse (billing, CRM, support tickets).
Enter Mitzu 🚀
Mitzu is an agentic product analytics platform that runs directly on your data warehouse. Here is what that means in practice:
Zero AI Hallucinations 🧠 — The agent doesn't write raw SQL. Instead, it assembles a precise analysis specification, and our deterministic query engine turns that into SQL using hardened product analytics methodology. Same question, same SQL, every time. No methodology errors slipping through.
Automatic Setup ⚡ — Our Configuration Agent scans your warehouse, identifies your event tables, and builds a semantic layer specialized for product analytics. No YAML, no manual hand-mapping.
Your Data Never Leaves 🔒 — No ingestion, no per-event pricing, and no data silos. Because it runs natively, Mitzu can effortlessly join product events to billing tables or CRM data in the exact same query.
⚠️ One Honest Qualifier
Mitzu requires a modern cloud data warehouse (Snowflake, BigQuery, Databricks, Redshift, or ClickHouse) with event data already sitting in it. If you're still figuring out your data stack, we're not the right fit just yet.
We'd love for you to check it out! I'm happy to answer any questions below about how the deterministic engine works, our semantic layer, the Slack and MCP integrations, or anything else on your mind.
— Istvan & the Mitzu team
About Mitzu on Product Hunt
“Agentic product analytics that runs on your data warehouse”
Mitzu was submitted on Product Hunt and earned 27 upvotes and 5 comments, placing #22 on the daily leaderboard. Mitzu is an agentic product analytics platform that runs on your data warehouse — built to answer the why, not just the what. Ask complex questions like "why did week-2 retention drop?" and the Analytics Agent investigates across funnels, cohorts, and segments, returning a synthesised answer. No hallucinated SQL: a deterministic engine produces methodology-correct queries every time. Your data stays in Snowflake, BigQuery, Databricks, Redshift, or ClickHouse.
Mitzu was featured in Analytics (171.9k followers), SaaS (42.1k followers) and Data & Analytics (5.6k followers) on Product Hunt. Together, these topics include over 61.4k products, making this a competitive space to launch in.
Who hunted Mitzu?
Mitzu was hunted by Ambrus Pethes. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Mitzu stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Ambrus Pethes
This is sick! Don't all of these warehouses have AI analysis built in? ie snowflake cortex? What advantage does Mitzu have over the in-house solutions?