From hypothesis to decision,
in one system of record.
ExperimentOps replaces the feature-flag hacks, disconnected analytics tools, and spreadsheets teams stitch together to run experiments -- with one system that owns configuration, assignment, monitoring, analysis, and the decision itself.
The workflow you're probably running today
Experiment setup, metric definition, monitoring, and interpretation are usually fragmented across analytics platforms, spreadsheets, and dashboards. No single system owns the experiment end-to-end.
Today, without ExperimentOps
- Variant assignment lives in a feature-flagging tool or ad-hoc code
- Exposure and conversion events are tracked in a separate analytics tool
- Significance gets computed in one-off dashboards or spreadsheets, inconsistently
- Decisions and rationale end up in a doc tool, disconnected from the data
With ExperimentOps
- One system owns configuration, assignment, monitoring, and analysis
- The same statistical method applied consistently to every experiment
- A searchable record of every experiment ever run, and why
- The decision and its rationale live next to the data that produced it
Every stage of the experiment lifecycle, owned end to end
Not a feature-flag system. Not a BI dashboard. One workflow, from the first hypothesis to the recorded decision.
Turn a hypothesis into a fully specified experiment
Set your hypothesis, variants, traffic allocation, audience targeting, attached metrics, and stopping condition -- one structured configuration instead of a scattered plan doc.
Hypothesis
Variants
Deterministic assignment, not another flag hack
ExperimentOps owns traffic allocation directly -- fixed-percentage variant assignment with optional audience-targeting rules, served through one assignment API your engineers can trust.
Deterministic assignment, keyed on subject ID
Watch a running experiment without waiting on a dashboard build
Live, interim counts while an experiment runs, plus guardrail-breach detection and automatic safety actions -- always labeled interim, never confused with a final result.
Exposures
InterimOne statistical method, applied consistently
A defensible, auto-computed significance read per metric per variant, plus exploratory segment analysis kept structurally separate from the confirmatory result.
Record the decision where the data lives
Ship, kill, iterate, or call it inconclusive -- with rationale, optional approval, and a written summary tied to the exact analysis snapshot it was based on, plus a full audit trail.
Decision: Ship
Approved