Ocrolus operates an AI-driven workflow platform for lenders, handling document classification, fraud detection, and cash flow analysis across small business, mortgage, and consumer lending. The stack reflects a data-heavy, distributed architecture (Kafka, Snowflake, PostgreSQL, Go, Java) built for transaction scale, while active hiring tilts heavily toward senior engineering (5 engineers, mostly senior/staff level) — indicating a push to modernize backend systems and handle millions of transactions, a pattern consistent with their stated pain point around scaling infrastructure.
Ocrolus builds an AI-powered underwriting platform for lenders, automating document analysis, fraud detection, and cash flow assessment across multiple lending verticals. The platform ingests financial documents, classifies them, extracts key data points, and surfaces risk signals to underwriting teams. The company serves small business, mortgage, and consumer lenders, with a clear go-to-market acceleration in mortgage lending (active projects include mortgage lender workflow improvements and mortgage solutions launches). Ocrolus operates across 201–500 employees from New York, with development presence in India and the United States.
Ocrolus runs on Kafka (streaming), Snowflake (data warehouse), PostgreSQL/MySQL (databases), Go/Java/Python (backend), and AWS/GCP (cloud). Frontend tooling includes Figma, JavaScript/TypeScript, and testing via Playwright and Cypress. Analytics delivered via Tableau and Power BI.
Headquartered in New York. Active hiring spans the United States and India, with 201–500 total employees.
Ocrolus'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.