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§ Private Profile · Berkeley, CA, USA
AI testing platform for enterprise AI teams, detecting risks in AI applications through statistical testing.
Based in Berkeley, California, Distributional is an enterprise software company developing an artificial intelligence testing platform designed to help engineering teams detect and address risks in AI applications prior to production deployment. The company has raised a total of $30 million in venture capital, which includes a $19 million Series A funding round completed in October 2024. This recent financing was led by Two Sigma Ventures, with additional participation from prominent institutional investors including Andreessen Horowitz, Oregon Venture Fund, and Operator Collective. The enterprise software provider began its initial commercial deployments in late 2024 and expects to scale its internal workforce to approximately 35 employees by the end of the calendar year. Distributional was founded in September 2023 by Scott Clark, who previously co-founded SigOpt and served as the general manager of AI software at Intel.
Distributional has raised $30.0M across 2 funding rounds.
Distributional has raised $30.0M in total across 2 funding rounds.
Distributional has raised $30.0M across 2 funding rounds. Most recently, it raised $19.0M Series A in October 2024.
| Date | Round | Lead Investors | Other Investors | Status |
|---|---|---|---|---|
| Oct 1, 2024 | $19M Series A | TWO Sigma Ventures | Andreessen Horowitz, Axiom Partners, ALI Tamaseb, Dcvc (data Collective), G2vp, Point72 Ventures, Project A, Tribe Capital, Valar Ventures, Y Combinator, Jeremy YAP, Keri Gohman, RON Pragides | Announced |
| Dec 1, 2023 | $11M Seed | Andreessen Horowitz, A16z Scout Fund | Atreides Management, Exponent Founders Capital, General Catalyst, Giant Ventures, Haystack, LEGO Ventures, LGF, Matrix, NOT Boring Capital, Otherwise Fund, Point72 Ventures, Redpoint Ventures, Sequoia Capital, Spark Capital, Anjney Midha, Annelies Gamble, Brendan Iribe, Dylan Field, Jeremy CAI, Karim Atiyeh, Mario Gabriele, Ryan Carlson, Sohail Prasad | Announced |
Distributional is a Series A-stage AI startup founded in 2023, headquartered in Berkeley, California, with a fully remote workforce across the US and Canada.[1][3] The company builds an active AI testing and analytics platform that enables AI product teams to identify, monitor, and mitigate risks in generative AI models and applications by analyzing production logs for behavioral signals like anomalies, changes, and outliers.[1][2][5] It serves enterprise customers in sectors such as consumer software, finance, biotech, and media, solving the critical challenge of AI reliability—where traditional testing falls short for non-deterministic models—by automating statistical tests, integrating into CI/CD pipelines, and providing dashboards for collaboration and triage.[2][3][4][5] With $30M raised ($19M Series A led by Two Sigma Ventures, plus seed from Andreessen Horowitz and others), Distributional shows strong growth momentum, planning to expand its team to 35 by late 2024 amid rising enterprise AI deployments.[1][3]
Distributional was founded in 2023 by Scott Clark (CEO, former VP/GM of AI at Intel and co-founder of SigOpt), Nick Payton, and Michael McCourt, drawing directly from their experience at SigOpt—an ML optimization platform acquired by Intel in 2020.[2][3][4] Clark's inspiration stemmed from AI testing pain points encountered at Intel (post-SigOpt acquisition) and earlier at Yelp, where he led software for ad-targeting, highlighting the need for scalable, production-ready testing beyond static checks or manual evaluations.[3][4] The team's decade at SigOpt, serving sophisticated enterprises, revealed gaps in flexible tools for ML pipelines, leading to Distributional's focus on generative AI reliability.[2] Early traction came swiftly: within a year, they secured $30M funding, beta customers from Fortune 100 firms, AI startups, and financial institutions, and partnerships validating testing as a top AI adoption barrier.[3][4]
Distributional rides the explosive growth of generative AI adoption, where enterprises face a "confidence gap" in model reliability—costing some firms millions daily due to unpredictable outputs amid rapid deployment.[2][4] Timing is ideal: as AI shifts to production at scale, regulatory pressures (e.g., safety/robustness) and market forces like compute abundance amplify demand for CI/CD-equivalent testing, mirroring software dev evolution but adapted for probabilistic AI.[4] It influences the ecosystem by enabling safer AI in high-stakes sectors, partnering with leaders to standardize evals/monitoring, and accelerating trustworthy AI—positioning it to lead a "massive shift" in data-driven products.[2]
Distributional is primed to dominate AI reliability testing as enterprises scale generative apps, with team expansion, commercial launches, and $30M runway fueling GPU-enhanced analytics and UI improvements.[3] Trends like AI agents, multimodal models, and stricter compliance will drive demand for its adaptive platform, potentially evolving it into a full MLops staple. Its influence could expand by setting de facto standards for production signals, empowering bolder AI innovation while minimizing risks—bridging the gap from hype to dependable enterprise reality.[2][4]
Distributional has raised $30.0M in total across 2 funding rounds.
Distributional's investors include Two Sigma Ventures, Andreessen Horowitz, Axiom Partners, Ali Tamaseb, DCVC (Data Collective), G2VP, Point72 Ventures, Project A, Tribe Capital, Valar Ventures, Y Combinator, Jeremy Yap.