Chef vs Luminai
Side-by-side comparison of AI visibility scores, market position, and capabilities
Progress Software (NASDAQ: PRGS) infrastructure automation platform for DevSecOps; acquired 2020 for $220M at $70M ARR — Chef Infra, InSpec, and Habitat competing with Ansible and HashiCorp for enterprise configuration management.
About
Chef is a Seattle-based infrastructure automation and configuration management platform — acquired by Progress Software (NASDAQ: PRGS) in October 2020 for $220 million cash, representing a 3x revenue multiple on $70 million ARR with 95% recurring subscription revenue — providing DevSecOps automation tools including Chef Infra (infrastructure configuration-as-code), Chef InSpec (compliance automation and security policy enforcement), Chef Habitat (application build, deploy, and runtime automation), and Chef Automate (enterprise dashboard for compliance and infrastructure visibility). Founded in 2008 by Adam Jacob and now operating as Chef by Progress within Progress Software's DevOps portfolio alongside Telerik, Kinvey, and OpenEdge.
US YC W20 enterprise workflow automation for insurance/financial services/govt at 16% handle time reduction and 60% faster onboarding; $58.
About
Luminai (formerly DigitalBrain) is a United States-based enterprise workflow automation platform — backed by Y Combinator (W20) with $58.1 million in total funding including a $33 million Series B in March 2025, a $20.7 million Series A in March 2022, and a $3.4 million seed from investors including Peak XV Partners, General Catalyst, Underscore VC, Craft Ventures, and Avra — providing mission-critical industries (insurance, financial services, healthcare, and government) with AI-powered workflow automation that handles complex, multi-step operational tasks end-to-end, reducing average handle time by 16%, cutting customer service agent onboarding time by 60%, and saving 25+ hours per month per agent. Founded in 2018, Luminai's AI automation platform deploys in enterprise environments where regulatory requirements and operational complexity make fully automated AI agents impractical without human oversight integration.
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