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Keewano
Tel Aviv company launching KeewanoDB, a database that keeps each entity's events in order so an AI agent can ask why something happened.
Product and data teams that want an agent to investigate a path, such as which users look like last month's churn, from the raw event history.
Teams whose questions are already answered by a dashboard, or shops that only instrument a few hundred event types and plan to stay there.
Verdict
Keewano is a Tel Aviv company that builds KeewanoDB, a database for AI agents. It keeps each entity's events together and in order, so a query does not have to reconstruct the sequence first. Product and data teams point an agent at questions that were not written into a dashboard ahead of time, such as which users are on the same path as the ones who churned. The company says that kind of question is why the database exists: a dashboard can show what happened, and the reason often lives in the sequence around it.
On September 15, 2026, Keewano said it raised a $12 million seed round led by Hetz Ventures, with a16z speedrun, Remagine Ventures, DIG Ventures, and angel investors (CTech). Mark Kardashov, Dima Karger, Pavel Bibergal, and Vitaly Bukhovsky founded the company in 2024. Kardashov and Bukhovsky previously built TestProject, acquired by Tricentis in 2019, and Devalore, acquired by Abra in 2022. Keewano says the system can query a quarter of a billion events in half a second and return a result an agent can use immediately. It also says most deployments elsewhere capture only a few hundred event types, because each extra type costs more to instrument and to query (CTech).
Score Breakdown
How Keewano scores in the categories that matter to its buyers.
Pricing
Keewano is selling KeewanoDB to teams that want agents to query event history. The seed round was $12 million (CTech).
The Field at a Glance
Where Keewano ranks among Analytics & decision automation vendors we reviewed, by Overall Score and relative typical engagement cost.
Keewano scores 6.7 in this peer set, below Alteryx (7.1), Dataiku (7.4), and Hex (8.2). Relative cost sits with an analytics system a data team has to stand up, under a broad enterprise suite.
Use-case matrix
| Use case | Fit | Notes |
|---|---|---|
| Why a customer churned, from the event path | Strong | The stated example is an agent comparing paths. |
| Agent-ready query results | Strong | Results are meant to come back in a form an agent can use. |
| Very large event scans | Mixed | The company cites a quarter of a billion events in half a second. |
| A finished dashboard for humans | Weak | The pitch is the questions a dashboard cannot hold. |
| Shops with only a few hundred event types | Weak | The design wants the surrounding sequence, which many teams never capture. |
Who it’s for
Good fit
- Teams pointing agents at why a metric moved
- Companies that already log rich, ordered product events
- Buyers who have outgrown pre-aggregated tables for those questions
Poor fit
- Analysts who only need a chart of a known KPI
- Teams that will not instrument more event types
- Buyers who need a stack of public customer references before a pilot
Review Excerpts
Below are excerpts from public reviews and coverage. Paid reviews and pay-for-play sites such as Clutch were excluded.
“KeewanoDB keeps one customer's events in order. That is why our agent can ask which users are on the same path as the ones who churned, without an analyst stitching the path together first.”
“We were trying to use AI agents to answer business questions like 'which of our users are on the same path as the ones who churned last month?' You could see what happened on any dashboard, but why it happened lived somewhere the databases couldn't reach.”
“Most of our product only emits a few hundred event types. KeewanoDB wants the whole sequence, and we do not have that history sitting around to load.”
Methodology
This page is an independent evaluation of Keewano for buyers comparing options in analytics & decision automation. AI Industry Reviews accepts no sponsorships, advertising, or pay-for-placement fees. Keewano did not pay for this review.
What we scored
The headline number is an Overall Score on a 0-10 scale. Eight criteria fall under it in two groups.
- Buyer outcomes (for analytics & decision automation)
- Questions an agent can ask
- Ordered event history
- Published speed claims
- Evidence from outside buyers
- Company & commercial
- Innovation & product leadership
- Project management & communication
- Pricing
- Contract fairness
Pricing measures whether the price looks fair for the value delivered, including packaging and renewal friction that show up in real buying cycles.
Score Composition
| Input | Weight | What it covers |
|---|---|---|
| Reviews | 40% | A proprietary read of what practitioners say about likes, complaints, and day-to-day use, including public review sites, forums, and private chat rooms. Paid reviews and pay-for-play sites such as Clutch are out of scope. |
| Product | 35% | Hands-on look at screens and workflows. |
| Pricing | 15% | Whether the price looks fair for what you get. |
| Docs & training | 10% | Docs, tutorials, and training material. |
How we balanced the evidence
The Overall Score is the simple average of the eight criteria. Recommendation language follows that score and the fit pattern described above.
Scope
Keewano is graded here as analytics & decision automation. Criteria scores can move as more review volume and product checks are added.