Prevalent AI, a nine-year-old enterprise data-fabric company, raised $22 million in growth funding from Integrity Growth Partners, marking its first institutional capital raise since founding. The company has grown profitably on customer demand alone until now, and will use the funding to expand sales, marketing, customer success, and extend its knowledge-graph technology beyond cybersecurity into wider risk and enterprise applications. Prevalent serves Fortune 500 banks, telecoms, and insurers, with ARR more than doubling over the past year.
Gartner forecasts that 40%+ of agentic AI projects will be scrapped by end of 2027 due to spiraling costs, murky business value, and inadequate risk controls. Prevalent AI's thesis: enterprises lack reliable, joined-up context for AI systems to act safely and effectively. The platform creates a sovereign knowledge graph from fragmented data sources, giving both human teams and AI agents a clear picture of existing systems, dependencies, and weak spots. Customer evidence is stark: one global insurer cut executive report time by 95%, another lifted incident detection by 80%. For infrastructure architects scaling agents, the practical implication is non-trivial: autonomous systems deployed on fragmented, uncontextualized enterprise data become liability vectors, not efficiency gains. Data fabric and knowledge-graph infrastructure is no longer a data-science luxury—it's becoming table stakes for safe agentic AI deployment at scale.