AI search startup Glean announced on Tuesday that it has reached a valuation of $7.2 billion following its latest funding round — the company’s third capital raise in under two years. This represents a valuation increase of nearly 57% since its previous round in September, where its value had already more than doubled in just over six months, highlighting continued strong investor demand for AI-driven companies.
The Palo Alto-based enterprise AI firm secured $150 million in this latest round, led by asset management firm Wellington Management. As public markets remain uncertain, many startups like Glean are choosing to remain private longer, raising significant late-stage funding. According to Michael Ashley Schulman, partner at Running Point Capital Advisors, “Founders avoid the volatility of public markets and employees receive secondary-market liquidity via structured rounds.”
Founded in 2019 by former Google search engineers, Glean has surpassed $100 million in annual recurring revenue in its last fiscal year. The company develops AI-powered search tools and large language models that provide businesses with personalized query responses, aiming to optimize enterprise productivity and internal information management.
Glean’s 72x valuation multiple on revenue is considered aggressive, but Schulman noted that investors are receiving “early access to a franchise,” particularly given that the company is currently cash-flow positive.
Earlier this year, Glean introduced its Glean Agents platform, which enables businesses to automate various operations through AI. The company expects the platform to facilitate 1 billion agent actions by the end of 2025. Industry leaders have pointed to AI-based agents as one of the most transformative applications of artificial intelligence. Microsoft CEO Satya Nadella has also highlighted how AI agents could disrupt the long-dominant software-as-a-service (SaaS) business model.
The AI sector continues to attract robust global investment as enterprises and governments pursue artificial intelligence for diverse use cases such as drug discovery, infrastructure management, and productivity enhancement.