Quaeris gives product teams instant access to engagement, retention, and cohort metrics-grounded in your governed semantic layer. Ask anything. Get sources cited.
14-min median insight From question to certified answer, not days
Zero hallucinations Agents query your semantic layer, not guesswork
Role-based access PM in NA sees NA data only, enforced at query time
Full audit lineage Question to source in one click, every time
Engagement, retention, funnel, and feature-impact answers - governed, auditable, and ready in seconds without writing a single line of SQL.
Quaeris surfaces engagement drivers across every feature, segment, and time window in plain language. PMs get ranked answers, not raw tables, with every metric certified against a single governed definition.
Cohort retention curves update automatically as new events land in your warehouse. Quaeris alerts your team the moment a week-over-week retention delta crosses a governance-defined threshold - no analyst dependency.
Quaeris unifies product events, CRM signals, and warehouse data into a single governed funnel so PMs can prove which features move the needle on activation, conversion, and expansion revenue.
Every number product teams see in Quaeris is traceable back to its certified source - from the natural-language question, through the approved metric definition, down to the exact warehouse table and join logic.
Product teams lose momentum when analytics latency outpaces decision velocity. Here's what's slowing you down-and how Quaeris fixes it.
You ask a retention question on Monday. Your data team builds it Friday. By then, the window has passed and you're on to the next issue. Product velocity gets crushed by analytics latency.
Type your question once. Quaeris agents interpret it, query your semantic layer, and return a certified answer with sources cited-with a median time to first insight of 14 minutes, not days.
One team's "active user" is another's "paid user." Your CEO's board presentation uses different retention math than your product spec. These inconsistencies compound into misaligned decisions.
Your data team owns the semantic layer. Every agent answer is locked to certified metric definitions-revenue, activation, churn, cohort size. Same definition, every time, every team.
Self-serve BI gives you speed but breaks compliance. Asking analysts gives you audit trails but kills productivity. You're stuck choosing between velocity and control.
Quaeris is governance-first by design. Role-based access is enforced at the agent level, not at the dashboard filter. Every query and answer is audited. Speed and compliance, not either-or.
From warehouse connection to certified insight in minutes. No SQL tickets. No analyst bottleneck.
Link Quaeris to Snowflake, BigQuery, Databricks, or Redshift. Your event data, user tables, and subscription facts become queryable through one governed semantic layer.
Warehouse connection diagramYour data team defines activated-users, retention-rate, churn-definition, cohort-window. These live in the semantic layer. Every agent answer locks to these definitions-no drift, no ambiguity.
Semantic layer edit UIType: "What is retention for users acquired in Q1 2026?" or "Cohort sizes by acquisition channel?" Quaeris interprets the question and queries the semantic layer-no SQL needed.
Agent chat interfaceThe answer shows engagement, retention, or cohort breakdown-plus the metric definitions and data lineage behind it. Role-based access means your product managers only see data they're allowed to see.
Answer card with sources citedFrom activation rates to LTV correlations-ask in plain English, get governed answers in seconds.
What is day-1, day-7, day-30 activation by cohort?
What is day-30 retention for high-value cohorts?
How many users progress through signup → activation → paid?
Does feature adoption correlate with lifetime value?
Two deployments that show how governed analytics changes the product org's relationship with data.
Challenge: Product team was writing 5–10 analytics requests per week. Each took 2–3 days. Team velocity on features plummeted because half the time went to waiting for data.
Solution: Deployed Quaeris with a 120-metric semantic layer linked to Snowflake. Gave product team read-access to the agent interface.
"Before Quaeris, we were our own bottleneck. Now I ask a question and get a cited answer in 10 minutes. Everything we ship is grounded in the same metric."- Head of Product, B2B SaaS (Mid-Market)
Challenge: Mobile, web, and in-store teams each had their own definition of "purchase" and "repeat customer." Board meetings were debates about methodology, not insights.
Solution: Federated all event definitions into a Quaeris semantic layer. Taught product teams to ask cohort and retention questions in plain language.
"Quaeris solved a problem we didn't know how to name: the audit trail of who asked what and why the numbers matter."- VP Product, Retail / eCommerce
Three principles that make Quaeris the only analytics platform safe for product teams at scale.
Quaeris agents query your semantic layer-they don't generate numbers. Your data team owns the definitions. Every engagement metric, every retention curve, every cohort breakdown is locked to definitions your team certifies.
Click any answer and trace it back: which metric definition was used, which warehouse table it queried, which business rule applied. Product managers can audit any number in one click. Executives see sources, not hunches.
Access policies aren't dashboard filters-they're enforced when the agent runs. Product managers in North America see US data only. Product managers in EMEA see EMEA data only. Nothing more. Every query is logged for audit.
Illustrative. Actual values vary by team size and deployment scope.
See how Quaeris compares to legacy BI dashboards and ad-hoc SQL workflows on the dimensions that matter to product teams.
| Dimension | Legacy BI Dashboard | Ad-Hoc SQL / Analyst | Quaeris |
|---|---|---|---|
| Speed to insight | Weeks to deploy, days to query | 2–5 days per request | 10–20 minutes, self-serve |
| Metric consistency | Different definitions per dashboard | Definitions live in analysts' heads | One semantic layer, always certified |
| Governance | Dashboard filters only; not enforced | Ad-hoc access; hard to audit | Query-time access control; fully audited |
| Who can ask questions | "Dashboard builders" only | Analysts and data engineers | Any product person; no SQL needed |
| Audit trail | "What dashboard was viewed" | Which analyst ran what; hard to trace | Every question, answer, and source metric logged |
| Compliance readiness | Weak; data may escape to Excel | Manual audit logs | Built-in lineage; EU AI Act ready |
Quaeris connects directly to your warehouse. No data migration. No ETL pipeline rebuilds. Your data stays exactly where it is-we query in place, enforce role-based access, and log every query.
Book a 30-minute demo. We'll show you how to connect your warehouse, define metrics once, and unlock self-serve analytics for your entire product org.
