What it sells
Open-source data observability for data teams
Business model breakdown
Buyer: who owns the budget?
UnverifiedData/analytics engineering leads (open-source dbt users upgrading to Cloud).
Trigger: what makes them buy now?
UnverifiedBroken dashboards/models and lack of trust in data feeding AI workflows; need for incident triage and coverage beyond dbt tests.
Workflow: what inputs become what output?
Detect anomalies with ML monitors and tests, triage incidents with lineage, document/govern metadata, let analysts add validations.
Economics: what it saves and how it charges
Open-source core drives adoption; paid Cloud priced per seats and environments/tables, with extra tables billed per 1K.
Distribution: how it reaches customers
Open-source community and self-serve 'Start free', plus demo-led enterprise sales.
Funding history and coverage
| Round date | Stage | Amount | Investors | Source |
|---|---|---|---|---|
| — | Y Combinator Winter 2022 | — | Y Combinator | ycombinator.com |
Profiles summarize public reporting and company websites. Business-model notes are MaxBC's reading of that material, not confirmed facts; unknowns are left blank rather than guessed. Updated 2026-10-12.