Skan AI captures how work is performed inside enterprises through observation software, then turns that activity into process context for AI agents and automation. Its stack pairs streaming infrastructure (Apache Flink, Debezium, StarRocks, RocksDB) with Python services on Kubernetes and the OpenAI API, pointing to a real-time event pipeline behind task detection and workflow segmentation. Hiring is accelerating and skews toward senior and lead engineering talent.
Skan AI is a privately held software company founded in 2018 and headquartered in Menlo Park, California. It builds a process intelligence product that observes desktop work, discovers processes, and segments workflows so enterprises can automate complex operations with AI agents. The company employs 201–500 people and hires in the United States and India. Its platform runs on Azure and GCP, connects to warehouses such as Snowflake, BigQuery and Amazon Redshift, and uses Salesforce for go-to-market operations.
Skan AI uses Python with FastAPI, Flask and Django REST Framework, PostgreSQL, MongoDB, Apache Flink, Debezium, StarRocks, Apache Spark, Angular, Docker, Kubernetes, the OpenAI API, and Azure and GCP.
Job posts point to LLM integration via OpenAI APIs, AI agent integration into enterprise systems, observation software for workflow capture, task detection, workflow segmentation and process discovery.
Skan AI is headquartered in Menlo Park, California and hires in the United States and India, with recruiting concentrated on senior engineering roles plus data, sales and support.
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Skan AI's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.
