Context is Key: Skan.ai Delivers AI to Enterprise Customers

AI enthusiasm is everywhere, but enterprise AI success is still surprisingly rare. The reason is simple: most AI systems are being trained on documentation, workflows, and system logs that describe how work is supposed to happen, not how it actually happens. That missing layer is context. And context is quickly becoming the most important prerequisite for successful enterprise AI.

Today, we're congratulating Skan AI on its $63 million Series C financing, co-led by us and our friends at Cathay Innovation. Since leading Skan's Series B investment in 2022, we've watched the team build a category-defining platform that captures the operational reality of enterprise work and transforms it into actionable intelligence for automation and AI.

When we first invested, Skan was built around a simple belief: you can't automate what you don't understand. Enterprise workflows are shaped by thousands of decisions, exceptions, and workarounds that rarely appear in documentation or system logs.

As AI agents move into the enterprise, that missing context has become the biggest barrier to success. Skan's platform captures how work actually happens, creating a living context graph that gives AI agents the operational understanding they need to deliver real-world results.

Just as CRM systems became the system of record for customers, platforms that capture the “context layer” of work will become the system of record for enterprise AI. Without it, agents hallucinate, fall over with exceptions, require constant human intervention, and fail to deliver measurable business outcomes.

Skan's momentum reflects the urgency of this opportunity. The company now works with seven of the ten largest U.S. banks, is trusted by nearly a third of the Fortune 50 and has processed more than 25 billion work signals and counting.

We're proud to continue supporting Avinash, Manish, and the entire Skan team as they help enterprises move from AI experimentation to AI outcomes.

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