Skan AI Observation-to-Agent Platform

Skan AI is a Menlo Park, California company that maps how work actually runs inside regulated enterprises such as banks, insurers and healthcare payers, so that automation and AI agents are built on real operations rather than documented procedures. It reports adoption by 7 of the top 10 US banks and 3 of the top 5 US insurers.

The Observation-to-Agent (O2A) platform captures how processes run across mainframe, legacy desktop, VDI, web and office tools without backend integration, keeping raw screens inside the customer's environment. It distills observations into a Context Graph of Work covering data, decisions and rules, then shows where time and value are lost. Products include Blueprint for AI roadmap and ROI modeling, Process Intelligence for process maps and bottlenecks, Engineering Intelligence, and work-aware agents governed by Agentic Operating Procedures.

• Zero-integration capture: observes work across mainframe, desktop, VDI, web and office tools.
• Context Graph of Work: distills observations into data, decisions and rules.
• Process Intelligence: process maps, variants and bottleneck identification.
• Blueprint: AI roadmap and ROI modeling for automation candidates.
• Work-aware agents: execute end to end under Agentic Operating Procedures.
• Privacy controls: in-environment processing, audit logs and user control over what is kept or erased.

A Vietnamese bank can observe loan operations and card dispute handling to find automation candidates before buying RPA. An insurer can map claims handling across legacy screens and train agents on real steps. A BPO provider can benchmark productivity across client processes.

Reveals how back-office work really runs across legacy screens that system-log process mining cannot see. The company claims a 30%+ average productivity lift, $500M in delivered value and six weeks or less from observation to a working agent. Data stays in the customer's environment, and SOC 2, ISO 27001 and ISO 42001 certification supports use in banks and insurers.

Many agentic AI projects stall because agents lack context on how work is really done, especially in banks and insurers with decades-old core systems. Observation-based process intelligence addresses this gap and is relevant to financial institutions in Vietnam and Southeast Asia that run legacy cores alongside new digital channels.

Based in Menlo Park, California. Has raised a $63M Series C. Published an Agentic Process Automation Manifesto in October 2025 and launched the Agentic Ontology of Work in February 2026. Certified SOC 2, ISO 27001 and ISO 42001; customers include Definiti.