Skan AI lands $63M Series C to capture the hidden layer of enterprise work

Skan AI secures $63 million Series C to map real work

Skan AI, a startup that builds a “context graph of work” by watching how employees interact with enterprise software, announced a ↑ 63 million Series C round co‑led by Cathay Innovation and Dell Technologies Capital. Citi Ventures, Bloomberg Beta, State Farm Ventures and Wipro Ventures also participated, pushing total funding to roughly $120 million.

New suite of products targets hidden workflow layer

The company launched Skan AI Blueprint and Skan AI Agents, extending its existing Skan AI Intelligence platform. Together they promise discovery, modeling and automation of enterprise workflows that traditional process‑mining tools miss.

“Everyone is obsessed with building a better driver. We think the bigger opportunity is building a better navigation system,” co‑founder and CEO Avinash Misra told VentureBeat.

Industry reports show only 8% of enterprises have AI agents in production, and up to 95% of pilots need redesign, according to Gartner and an MIT study cited by Reuters. Misra argues the gap stems from relying on official process documents while ignoring how work actually happens on screens.

Skan’s technology installs lightweight observation agents on employee desktops, capturing screen transitions across spreadsheets, CRMs, email clients and legacy mainframes. The system abstracts these traces into a living model of business processes.

Unlike backend log‑based mining, which only sees completed transactions, Skan claims the “in‑between” actions hold the richest AI signal. “Eighty percent of what you need for AI execution lies between those systems,” Misra said.

Privacy concerns are addressed through aggregation: data is anonymized, scoped to selected applications, and never leaves the corporate firewall. Only statistical patterns across hundreds of users are surfaced, a design validated by European works councils and Bloomberg.

The firm reports over ↑ 500 million in cumulative customer value, including a U.S. bank that saved $18 million annually after cutting transaction costs by 32% and boosting throughput 41%.

Customers now include Unum, Mitie and several of the top ten U.S. banks. Revenue growth exceeded ↑ 300% year‑over‑year for the second straight year, with net dollar retention around 150%.

Intel provided by: Lyra Valance

Digital Assets & Web3 Insider