Memory layer
for experiments
Converise is Experimentation OS. One place to plan, analyze, decide, and remember which experiments actually moved the business.
The problem
Experimentation scattered across tools and teams
Ideas live in decks, results in three different tools, and every report waits for an analyst.
Without ConveriseWith Converise
- Without Converise: Experiments scattered across tools, teams and documentsWith Converise: One backlog, timeline and kanban across every team
- Without Converise: Every report waits for scarce analyst capacityWith Converise: Automated reports, quality checks and alerts on every review
- Without Converise: Results get questioned - hard to prove a win is realWith Converise: Every risk flagged and explained, with the numbers behind it
- Without Converise: Learnings are lost and tests get repeatedWith Converise: A decision log that flags hypotheses already tested
Every experiment in one registry
Every test from every team, whatever it runs on - with the status, the recommendation and the decision that was actually made.
- Hypothesis, variants, KPIs and guardrails
- Status and latest decision on every row
- Alerts when a running test needs a look
See what runs and when
Planned and actual timeframes on one track, so what is live, what is finished and what is still coming is one view - not a status round. Timeline, list and kanban views of the same registry.
Connect the data
Connect once and every experiment gets its evidence on its own - results refreshed on a schedule, quality checks run, a recommendation ready and an alert when something needs a look.
- BigQuery, Databricks and Snowflake today
- Manual entry - the same checks, no connector needed
- More tools coming soon
Effects with the statistics stated, not implied
Primary and guardrail KPIs side by side - lift, p-value and a confidence interval on every row.
- Know whether a win is real before you ship it
- The guardrail sits next to the win - no second report to reconcile
- When the data can't support a verdict, you are told instead of left guessing
Find where the treatment helps - and where it hurts
Scan the warehouse for segments and pairs where the effect differs, corrected for multiple comparisons, and see them before you roll out. Exploratory by design. Roll out only to the segments that win, hold back the ones that lose.
Risk checks before you trust a result
16 checks run on every review, catching the problems that quietly invalidate a result before anyone calls a winner.
A recommendation you can argue with
Ship, reject, iterate, investigate or keep running - with confidence, the blocking risks and the next actions spelled out.
Organizational memory that compounds
Every decision, its rationale and the rollout outcome stay searchable - losing hypotheses don't get quietly retried.
- Decision log with call and confidence
- Log post-rollout outcomes
Plan. Analyze. Decide. Remember.
Three steps from idea to a decision on the record.
Plan
Capture hypothesis, owner, variants, KPIs and guardrails, and size the test before it launches.
Analyze
Connect a warehouse table once or enter the results manually. KPI and segment effects, with source lineage, refreshed on schedule.
Decide & remember
Get a recommendation with risks and confidence, log the decision, track the rollout outcome.
Built for your seat
Five roles touch the same experiment - here's what changes for each.
Common questions
Didn't find yours?
support@converise.ioWho is it for?
Anyone who works on A/B tests - whether that is a few experiments a quarter or a large enterprise program. Product, growth, CRO and analytics people who need a call they can defend later, not another dashboard.
Does Converise replace Google Analytics, Amplitude or Optimizely?
No. Converise is the decision and memory layer above them - it normalizes their results and tells you whether the decision is safe. It doesn't run your tests.
What can I connect?
Today you can connect data from BigQuery, Databricks and Snowflake plus manual entry. More sources and tools (connectors, MCPs) coming soon.
Do you store our raw event data?
No. When you connect a warehouse, the SQL runs there and only normalized summary evidence and source lineage come back - no raw data is downloaded or stored in our database. Without a warehouse you enter summary results directly, so there is no raw data in the first place.
We only run a few tests a month. Is this overkill?
No - fewer tests make each one matter more. The checks catch a broken test before you act on it, and next quarter's test starts from what this one taught you. One honest caveat: with small samples you will see more keep running and iterate than ship, because that is what the evidence supports.
Is it available now?
Yes. Create a free account - early access is free, no credit card.
My tool isn't on the list.
Converise is in early access and we are adding integrations as people ask for them - more warehouse connectors, tool integrations and MCP imports are in the works. Every request shapes the order, so tell us what you use at support@converise.io.
Your next experiment result, safe to ship
From an empty account to a reviewed experiment in one sitting.