Skan AI has raised $63 million in a Series C funding round to further develop its unique process intelligence platform, which records and analyzes how work flows through enterprise systems. The company’s technology captures anonymized usage metadata from employee desktops to create precise operational maps that feed AI agents aimed at cutting costs and boosting throughput.
- Raised $63M to enhance AI-powered enterprise workflow mapping platform
- Platform monitors 25 billion work signals while preserving data privacy
- Clients report 30-40% average operational cost savings and millions in annualized value
Market signal
Skan AI’s latest $63 million funding round highlights strong investor confidence in process intelligence as foundational infrastructure for enterprise AI. Their platform uniquely captures direct observational data about employee workflows, distinguishing itself from competitors relying on system logs or documents. This approach enables highly accurate mapping of multistep processes across systems and teams.
The company reports rapid revenue growth exceeding 300% year-over-year and an impressive net dollar retention rate of 150%, indicating expanding usage within its substantial global customer base. With over 25 billion work signals already processed, Skan AI is positioning itself as a key enabler of AI-driven operational efficiency in sectors including financial services, insurance, healthcare, and technology.
Operator impact
Skan AI’s platform helps enterprise operators gain unprecedented visibility into how work is actually performed, surfacing bottlenecks and sources of inefficiency without compromising sensitive content. By leveraging anonymized metadata derived from locally processed screenshots, organizations can map complex workflows while maintaining strict data privacy controls.
Clients have realized significant operational improvements, such as a major U.S. bank that identified $37 million in friction and achieved a 32% reduction in cost per transaction alongside a 41% throughput increase using Skan’s AI agents. Across customers, reported average savings range from 30% to 40%, demonstrating the platform’s impact on reducing operational friction and accelerating AI-driven task automation.
What to watch next
With this new funding, Skan AI plans to intensify product development and expand sales efforts targeted at financial services, insurance, healthcare, and technology sectors. Observers should monitor how effectively the company scales deployment across these complex industries and whether its model of direct workflow observation sets a new standard for enterprise AI infrastructure.
The evolving role of AI in identifying and automating enterprise inefficiencies positions Skan AI’s platform as a critical navigation system for operational improvement. Buyers and operators need to evaluate the platform’s ability to integrate with existing systems while maintaining data privacy, and track emerging competitor solutions attempting to replicate or improve upon this observational approach.