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Deepchecks
ML and LLM testing, CI evaluation, and production monitoring platform (Know Your Agent). Check Point acquired Deepchecks’ team and intellectual property in May 2026.
Teams that want automated LLM/agent evaluation in CI and production monitors with a testing-first workflow rather than a pure tracing desk.
Buyers who need a long-horizon independent vendor roadmap, or who only want a lightweight open-source tracer without enterprise eval packaging.
Co-founded by Philip Tannor.
Verdict
Deepchecks fits ML and LLM teams that want evaluation and monitoring with a testing posture (CI gates, version scoring, agent reports). Public packaging uses Basic, Scale, and Enterprise with DPU and seat limits; dollar rates are quote-led, with AWS Marketplace listing a ~$40k/year contract signal for a small starter pack. Practitioner feedback is thinner than Arize or Fiddler. Check Point’s May 2026 acquisition of the team and technology is the main commercial risk for new independent contracts.
Score Breakdown
How Deepchecks scores in the categories that matter to its buyers.
Pricing
Deepchecks publishes Basic, Scale, and Enterprise packages on deepchecks.com/pricing with seat, application, and DPU limits, but does not list public dollar rates. As of September 2026.
Model: quote-led DPU and seats. Basic targets small teams (about 3 seats, 1 app, 5k DPUs/month). Scale expands seats, apps, and DPUs with premium support. Enterprise adds custom limits, security, and dedicated success. AWS Marketplace has listed a ~$40,000/year starter contract for up to 5k DPUs/month (treat as a channel figure). Check Point’s May 2026 team-and-IP acquisition may change packaging; confirm current contracting path before budgeting.
The Field at a Glance
Where Deepchecks ranks among Observability & monitoring vendors we reviewed, by Overall Score and relative typical engagement cost.
Deepchecks scores 6.7, behind Arize AI (7.7) and Fiddler AI (8.1). Its relative cost is higher because packaging is enterprise-quoted and has no $50 Pro seat.
Use-case matrix
| Use case | Fit | Notes |
|---|---|---|
| CI evaluation gates for LLM apps | Strong | The product is built around testing. |
| Production LLM monitoring | Strong | Monitoring is hosted and metered in DPUs. |
| Open-source local tracing only | Mixed | It has open-source roots, but the commercial product is what you buy. |
| Long independent vendor roadmap | Weak | Check Point acquired the team and IP in May 2026. |
Review Excerpts
Excerpts from company materials and public coverage of Deepchecks, plus representative buyer views drawn from public information. Paid reviews and pay-for-play sites were excluded.
“Deepchecks LLM Evaluation is an enterprise-grade AI testing, observability and monitoring platform that provides visibility, control, and trust across AI systems in production.”
“Running the agent report in one click and getting a single scorecard saved our team review time.”
Representative buyer view
“Public dollar tiers are not listed on the pricing page, so we had to go through sales to compare it with open-source eval stacks.”
Representative buyer view
“After the Check Point announcement we were unsure how the roadmap and our contract would continue.”
Representative buyer view
Where customer reviews couldn't be found, our analysts attempted to give a voice to buyer sentiment, drawing on real information from review sites, forums, and product documentation.
Based on: Deepchecks’ pricing page and Calcalist’s report on the Check Point acquisition
Company Facts
- Founded
- 2019 (CB Insights)
- Headquarters
- Ramat Gan, Israel (CB Insights)
- Total funding raised
- $14M (CB Insights)
- Key investors
- Check Point, Alpha Wave Global, Grove Ventures, Hetz Ventures, Intel Ignite (CB Insights)
- Website
- deepchecks.com
Key Leadership
Philip Tannor
Co-founder and CEO
Methodology
This page is an independent evaluation of Deepchecks for buyers comparing options in observability & monitoring. AI Industry Reviews accepts no sponsorships, advertising, or pay-for-placement fees. Deepchecks 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 observability & monitoring)
- CI / LLM evaluation harness
- Production monitoring
- Agent / KYA reporting
- Vendor continuity clarity
- 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 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 use-case matrix above.
Scope
Deepchecks is graded here as observability & monitoring. Criteria scores can move as more review volume and product checks are added.