Distributional, founded by former Intel AI Software General Manager Scott Clark, recently completed a $19 million Series A funding round led by Two Sigma Ventures.

Clark told TechCrunch that the inspiration for Distributional came from the testing issues he encountered while applying AI at Intel and his experience as a software director in the ad targeting department at Yelp. He emphasized, "As the value of AI applications continues to rise, so does the operational risk it brings. Our platform helps AI product teams proactively and continuously detect, understand, and resolve AI risks, preventing them before they occur."

Funding, Investment

Clark joined Intel through an acquisition. In 2020, Intel acquired SigOpt, a model experimentation and management platform co-founded by Clark. In 2022, Clark was appointed Vice President and General Manager of Intel's AI and Supercomputing Software Division. During his tenure at Intel, Clark and his team frequently faced issues with AI monitoring and observability.

Clark noted that the non-deterministic nature of AI means that the same input can yield different outputs. Coupled with the fact that AI models rely on various factors such as software infrastructure and training data, finding errors in AI systems becomes extremely difficult.

According to a 2024 survey by the Rand Corporation, over 80% of AI projects ultimately fail. Generative AI is particularly challenging for enterprises, with Gartner predicting that one-third of deployments will be abandoned by 2026.

To address these issues, Clark created Distributional, aiming to streamline AI auditing. The platform can automatically create statistical tests for AI models and applications based on developers' specifications and organize the test results in a dashboard. Users can collaborate on the test "repository" on the dashboard, categorize failed tests, and recalibrate them if necessary.

Distributional provides cross-organizational visibility, allowing users to understand what, when, and how AI applications are tested, and how these tests evolve over time. Clark said, "We provide a repeatable process for AI testing, using shareable templates, configurations, filters, and labels that can be applied to similar applications."

Although there are already AI experimentation solutions like Kolena, Prolific, Giskard, and Patronus on the market, Clark believes Distributional offers a more "white-glove" experience. The company handles customer installation, implementation, and integration, along with AI test troubleshooting services.

Distributional, which has just completed its Series A funding, plans to expand its technical team, focusing on UI and AI research engineering. Clark expects the company to grow to 35 employees by the end of the year, with the first enterprise deployments starting.

In addition to Two Sigma Ventures, Andreessen Horowitz, Operator Collective, Oregon Venture Fund, Essence VC, and Alumni Ventures also participated in this round of funding. So far, the startup headquartered in Berkeley, California, has raised $30 million in funding.