Vellum raises $20M Series A led by Leaders Fund, joined by Socii Capital, Y Combinator, Rebel Fund, and others.

Vellum raised $20 million in Series A funding led by Leaders Fund, with participation from Socii Capital and existing investors. The funding will accelerate Vellum's product innovation and global expansion, addressing the enterprise gap where 54% lack a comprehensive AI strategy. Vellum's platform helps companies like Drata and Swisscom operationalize AI, offering a centralized control panel for AI workflows, testing, and deployment, ensuring reliability and compliance.

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More. 2025 is anticipated to be the year AI gets real, bringing specific, tangible benefit to enterprise. However, according to a new State of AI Development Report from AI development platform Vellum, we’re not quite there yet: Just 25% of enterprises have deployed AI into production, and only a quarter of those have yet to see measurable impact. This seems to indicate that many enterprises have not yet identified viable use cases for AI, keeping them (at least for now) in a pre-build holding pattern. “This reinforces that it’s still pretty early days, despite all the hype and discussion that’s been happening,” Akash Sharma, Vellum CEO, told VentureBeat. “There’s a lot of noise in the industry, new models and model providers coming out, new RAG techniques; we just wanted to get a lay of the land on how companies are actually deploying AI to production.”Enterprises must identify specific use cases to see successVellum interviewed more than 1,250 AI developers and builders to get a true sense of what’s happening in the AI trenches. According to the report, the majority of companies still in production are in various stages of their AI journeys — building out and evaluating strategies and proofs of concept (PoC) (53%) beta testing (14%) and, at the lowest level, talking to users and gathering requirements (7.9%). By far, enterprises are focused on building document parsing and analysis tools and customer service chatbots, according to Vellum. But they are also interested in applications incorporating analytics with natural language, content generation, recommendation systems, code generation and automation and research automation.So far, developers report competitor advantage (31.6%), cost and time savings (27.1%) and higher user adoption rates (12.6%) as the biggest impacts they’ve seen so far. Interestingly, though, 24.2% have yet to see any meaningful impact from their investments. Sharma emphasized the importance of prioritizing use cases from the very start