Harness, which uses AI to automate code testing, verification, security, and governance, raised a $240M Series E led by Goldman Sachs at a $5.5B valuation
AI DevOps tool Harness, founded in 2017 by serial entrepreneur Jyoti Bansal, is on track to exceed $250 million in annual recurring revenue in 2025, Bansal tells TechCrunch.
Context & Ripple Effects
Harness has progressed from a 2017 launch to successive financing for continuous delivery and integration, including its $85M Series C for its engineering and DevOps platform and a later $175M Series D plus debt financing. The new round extends that funding arc while broadening the product framing toward AI-assisted testing, verification, security, and governance.
The reported revenue trajectory makes this more than an early-stage AI tooling bet: it is capital going to an established DevOps vendor as software teams seek automation with operational controls. That positioning overlaps with the wider need for automated compliance workflows, though Harness is focused on the software delivery lifecycle.
First-order effects
- Harness receives $240M of new capital and a $5.5B valuation, giving it more capacity to invest in and sell its AI-enabled DevOps suite.
- Goldman Sachs becomes the lead investor in a company that says it is approaching more than $250M in 2025 annual recurring revenue, signaling institutional backing for the business at its current scale.
Second-order effects
- Rival DevOps and developer-tool vendors face added pressure to pair AI coding and automation features with verification, security, and governance rather than treat them as separate products.
- Enterprise buyers evaluating AI-assisted software delivery gain a better-capitalized vendor option centered on controls, potentially raising expectations that automation tools can satisfy engineering and governance teams together.
Third-order effects
- If enterprises continue to adopt AI across delivery workflows, the durable advantage may accrue to platforms that combine automation with auditable controls, not to point tools that automate a single development task.
- The financing suggests later-stage capital may increasingly favor AI software vendors with demonstrated recurring revenue and a clear path into regulated or controlled operational workflows; whether that becomes a broad funding standard remains uncertain.
The trend: AI is moving from isolated developer assistance toward governed automation embedded in the systems enterprises use to build, test, secure, and release software.