From warehouse data to a decision-safe readout.
Stop rebuilding the same analysis for every test. Connect the data once, let results refresh on a schedule, and share standardized readouts with the caveats attached — instead of another one-off spreadsheet.
Warehouse-firstYour raw data stays putFree during early access
Built for analysts who sign their numbers
Native connectors: BigQuery, Databricks, Snowflake
Standardized, explainable statistics
Raw data never leaves your warehouse
Native connectors for modern data platforms
BigQuery
Databricks
Snowflake
Google Analytics 4soon
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Optimizelysoon
Notionsoon
ConfluencesoonThe problem
Every readout starts from scratch
You spend more time finding the test setup than analyzing it. Everyone wants the result, nobody logs the hypothesis — and the same methodology debate restarts on every second test.
Without Converise
- Chasing test context — dates, variants, owners — by hand
- A fresh query and spreadsheet for every single readout
- Stakeholders questioning methodology and numbers
- Ad-hoc report requests interrupting deeper work
With Converise
- Every experiment arrives with its context already attached
- Connect the data once — results refresh on a schedule
- One consistent, explainable methodology for every test
- A shareable readout that answers the questions for you
What you get
The analysis you'd defend, automated
Connect
Native connectors to your data platform
Bind an experiment to your warehouse once — BigQuery, Databricks or Snowflake — and evidence flows in on a schedule. No warehouse? CSV/JSON upload and a simple API cover the rest.
- BigQuery, Databricks and Snowflake supported today
- Set up once, refresh automatically
- Only summaries are stored — raw data stays in your warehouse
Check
The checks you'd run by hand, run every time
Every review runs a battery of automated quality checks — randomization, sample size, guardrails and more — so a broken test gets caught before it becomes a decision.
- Automated checks on every single review
- Blocking risks listed in plain language
- Segment findings ship with their caveats attached
Share
A readout nobody can misquote
Effects, checks, recommendation and data source in one report — shareable as a link or exported as a memo. The number a stakeholder quotes is the number you computed.
- One report page per experiment, always current
- Decision memo export for stakeholders
- Every figure keeps a reference to its source
How it works
Three steps, no migration
Connect the data
Point an experiment at your warehouse table — or upload CSV/JSON, or push through the API.
Let it refresh
Evidence updates on a schedule and every refresh re-runs the checks automatically.
Share the readout
Standardized effects, warnings and a recommendation — in a report you can link, not rebuild.
FAQ
Questions from your seat
Do you ingest our raw event data?
No. The heavy lifting happens in your warehouse and only summary results are stored. Raw events and user identifiers never leave your platform.
I can do all of this myself in SQL and notebooks.
You can — once. Converise turns that one-off work into a standing pipeline: same methodology, every test, refreshed automatically, with a report that answers stakeholder questions without you.
Will the statistics match our internal standards?
The methods are standard, deterministic and fully explainable — and every result shows which method was applied and why. Same evidence in, same numbers out, reproducible on your side.
Which platforms are supported?
BigQuery, Databricks and Snowflake natively, with CSV/JSON upload and a REST API for any other source. More connectors follow real workflows, not logos.
Standardized, explainable statistics for every experiment.
Connect once, refresh on schedule, and ship readouts your future self can reproduce.
Free during early accessNo credit card