Skan AI has raised $63 million as the enterprise AI company expands a platform that gives AI agents operational context based on how employees and business processes actually work.
The round was co-led by Cathay Innovation and Dell Technologies Capital, with participation from Citi Ventures, Bloomberg Beta, State Farm Ventures and Wipro Ventures.
The financing coincides with the launch of Skan AI’s broader enterprise AI platform and the general availability of Skan AI Blueprint and Skan AI Agents.
Together with Skan AI Intelligence, the products are designed to provide enterprises with a continuous view of how work is performed and use that information to deploy AI agents grounded in actual operational processes.
Skan AI argues that one of the major barriers to enterprise AI adoption is not simply the quality of underlying models, but the absence of reliable context about how work happens across people, applications, workflows and exceptions.
Rather than relying exclusively on documents and system logs, Skan AI observes work patterns and converts those signals into a context graph that can be used by AI systems.
The company said it has delivered more than $500 million in measured customer value by applying that approach.
Skan AI reported growth of more than 300% year over year and average net dollar retention of 150% as customers expanded deployments across their organizations.
The company has processed more than 25 billion work signals and now works with seven of the 10 largest U.S. banks.
Skan AI also said its technology is deployed within one-quarter of the Fortune 50.
The company’s platform is powered by NVIDIA AI Enterprise and NVIDIA NIM microservices.
Skan AI Blueprint is designed to discover and prioritize AI opportunities across enterprise systems, including legacy applications and regulated workflows.
Skan AI Intelligence provides process benchmarking, workforce management information and identification of potential automation and technology opportunities.
Skan AI Agents uses the company’s observed work context to execute processes autonomously, with agents trained against actual examples of work and designed to operate with human oversight and auditability.
One deployment cited by the company involved a major U.S. bank where Skan AI observed 11.2 million context switches across approximately 1,500 finance professionals.
Skan AI said the analysis identified $37 million in operational friction.
The resulting AI implementation reduced cost per transaction by 32%, increased throughput by 41% and generated $18 million in annualized savings, according to the company.
Skan AI recently partnered with the University of Missouri on research examining the intersection of artificial intelligence, enterprise systems and human work.
The company positions its technology as a context layer capable of capturing institutional knowledge that may not be reflected completely in traditional enterprise data sources.
KEY QUOTES:
“Everyone is obsessed with building a better car. We think the bigger opportunity is building a better navigation system.”
Avinash Misra, Co-Founder And CEO Of Skan AI
“Enterprise work context is becoming the foundational infrastructure layer for enterprise AI, the same way CRM became the system of record for customer relationships. Skan AI is the only company we have seen that builds that context from direct observation of work itself and carries it all the way through to agents running in production. With a fourth of the Fortune 50 already running on Skan AI, we believe this is one of the defining platform companies of the next decade.”
Simon Wu, Partner At Cathay Innovation
“A financial institution’s real differentiation isn’t its products, it’s the decades of experience and operational know-how that shape how things get done internally. With NVIDIA platform, Skan AI observes thousands of real cases to capture how the enterprise’s best performers operate, then turns that into agents that run the work their way, all while running on infrastructure the financial institution owns and controls to be governed and auditable at every step.”
Aser Blanco, Global Head Of Banking At NVIDIA
“Skan AI has been an important partner helping us better understand how work actually happens across our operations. Their technology gives us unprecedented operational visibility that has dramatically accelerated our AI transformation. We’re excited to continue working together as we scale what’s possible with AI across the business.”
Cijo Joseph, Chief Technology & Digital Officer At Mitie
“The mandate for enterprise leaders right now is to identify where AI can create measurable operational advantage. That question cannot be answered unless the organization has a clear understanding of how work really gets done. Skan AI has built the observation and context layer that provides that understanding, helping enterprises deploy AI more effectively and move from experimentation to measurable impact. We’re proud to support them as they continue to define this category.”
Raman Khanna, Managing Director At Dell Technologies Capital
“We invest in durable advantages, and Skan AI is building an important layer of enterprise business technology by helping organizations connect the information and context behind how work gets done. That foundation can help businesses improve collaboration, increase productivity and helps maximize the value of technologies used every day.”
Kate Strubhar, Executive At State Farm Ventures
