Selector raises $32M as AI observability startup doubles valuation to $375M amid fortune 1000 growth

Enterprise networks don’t fail quietly. When outages hit telecom carriers, cloud providers, or healthcare systems, costs can run into the millions per hour. That pressure is fueling a new wave of AI infrastructure startups promising to detect issues before they spiral. Selector just raised $32 million to prove it belongs in that category.

The Santa Clara–based AI startup announced Tuesday that AVP led a new funding round alongside Ansa Capital, Two Bear Capital, Sinewave Ventures, Singtel Innov8, and existing backers. The raise doubles Selector’s valuation to $375 million.

The timing is backed by strong numbers. Selector says cumulative annual recurring revenue reached 230% of 2024 levels, marking the fourth straight year the company doubled ARR. New ARR booked hit 370% of last year’s total. Roughly 80% of customers now come from the Fortune 1000, with three new Fortune 20 companies added across manufacturing and healthcare.

That traction matters in observability, a market crowded with monitoring dashboards that often generate more alerts than answers. Selector’s pitch is different: correlate data across the entire stack horizontally, rather than forcing teams to jump between siloed tools. Its system combines large language models, knowledge graphs, and causal reasoning to surface root causes instead of symptoms.

With $32M in Funding, AI Observability Startup Selector Doubles Valuation as Enterprise Demand Surges

The company recently secured eight foundational U.S. patents covering causal inference, LLM training, AI-driven correlation, predictive maintenance, and network path intelligence. The patents add weight to its claim that it’s building defensible technology rather than layering AI on top of existing alert systems.

“Selector’s ability to deliver consistent, strong growth while serving the world’s most complex Fortune 20 networks is a testament to the team’s execution and the mission-critical nature of the platform,” said Alex Scherbakovsky, general partner at AVP. “By providing one platform and one shared operational view, Selector helps enterprises understand and troubleshoot complex infrastructure challenges in real time. We are excited to partner with Selector to support the company’s international expansion and continued product innovation.”

CEO Kannan Kothandaraman says enterprises are shifting away from fragmented monitoring stacks and consolidating around platforms that combine intelligence, context, and automation.

“The increased adoption by Fortune 20 and Fortune 1000 organizations underscores the trust customers are placing in Selector,” said Kothandaraman. “Enterprises are moving away from fragmented monitoring tools toward platforms that deliver intelligence, context, and automation at scale, and our rapid customer expansion validates our efforts to help them navigate this transition and modernize their operations.”

Selector plans to use the new capital to accelerate product development and expand internationally. The company has already entered the Japanese market, securing regional partnerships and onboarding its first enterprise customers there. Distribution through major cloud marketplaces has widened its global footprint.

The next release focuses on agentic ChatOps, providing operations teams with multi-turn reasoning and iterative investigation capabilities within chat workflows. The goal is to shorten the mean time to resolution and reduce downtime before it spreads across systems.

Observability has shifted from dashboards to decision engines. Enterprises no longer want more alerts. They want fewer incidents. Selector’s latest round signals that investors believe AI-driven root cause analysis is becoming a core layer of enterprise infrastructure, not just another tool in the stack.

For a company that has doubled revenue four years in a row and now counts most of its customers among the largest enterprises on the planet, this raise looks less like a bet and more like an acceleration phase.