Now, harnessing this new appetite for tech investing, one of the newer startups to build a business around selling tech tools is announcing a significant fundraise that underscores how buzzy this part of the startup world has become.
The company announces its first major tranche of funding today: Harness said it has raised $240 million in financing co-led by Alkeon Capital and IVP, with participation from new investors Battery Ventures, Citi Ventures, Norwest Venture Partners, Sorenson Capital and Thomvest, along with existing investors Menlo Ventures and Unusual. The money will be used in part to continue expanding its platform — its last round was just in March (a COVID-19 strategic investment) — but also to start building on some momentum after seeing significant growth of its own.
- Details of the Funding Round Structure and Valuation
- Addressing the After-Code Bottleneck in Delivery
- How the Harness Platform Works Across the SDLC
- Traction to Date and the Competitive Landscape
- Global Expansion Strategy and Upcoming Hiring Plans
- Why This Funding Round Matters for the Company Today
- Outlook for the Business and the Company’s Path to IPO
Harness now has revenues standing at over $20 million ARR ($4 million ARR when they last raised money earlier this year), which puts the company’s valuation at approximately $500 million post-money (~25x ARR). That is not only up significantly from where it was less than a year ago — their Series B raise at $60+ million pre once again shows 20% growth month-on-month since then! — but an even starker contrast to estimates IVP showed me that overall software spend will shrink by almost half for many companies within eight years’ time. This number aligns well against other strategics giving feedback. As artificial intelligence becomes more interrelated across many aspects of computing work — from “traditional” programming use cases spanning analysis to security, through predictive analytics and much more — AI’s ability to accurately predict outflows tied directly or indirectly to generating revenue without stripping away value metric by value metric means we are seeing volume as an industry increase exponentially.
Details of the Funding Round Structure and Valuation
Series E features a $200 million primary investment from Goldman Sachs and an anticipated $40 million employee tender offer with involvement of new investor IVP, along with existing investors Menlo Ventures and Unusual Ventures. The tender liquidity offers long-tenured staff some liquidity while maintaining capital for growth, a phenomenon that’s become more common among late-stage private companies competing for senior engineering talent.
The raise reflects a 49% increase from its last valuation of $3.7 billion and makes for a total equity financing of $570 million. Those figures for a DevOps platform are indicative of the investor belief that now the real bottleneck in AI-era software development sits after code is written, where risk and cost congeal.
Addressing the After-Code Bottleneck in Delivery
As coding copilots crank out code faster, the downstream workload swells: unit tests and integration tests, security checks, policy conformance checkpoints, change approval processes, rollout strategies and observability. Enterprises tell us this post-code phase can consume up to 70% of engineering time, and a single misconfigured deployment can have huge downstream effects throughout production systems.
Harness, instead of just offering code suggestions, offers tools meant to check, regulate, and safely ship the code — bridging the divide between AI-generated changes and production reliability. The pitch appeals to regulated industries and massive platforms where throughput and guardrails need to march in lockstep.
How the Harness Platform Works Across the SDLC
At the heart is a software delivery knowledge graph that traces code changes, services, environments, deployments, tests, incidents, policies and costs. That graph supplies Harness’s AI agents with context to create pipelines and controls unique to each customer’s architecture and governance model, rather than using generic best practices.
An orchestration engine translates those AI recommendations into automated actions — running tests, invoking security checks, gating rollouts, triggering progressive delivery strategies — with safety built in. There is human-in-the-loop oversight by design: engineers, compliance teams or auditors can check AI-generated tests, repairs and policy updates before they’re implemented.
The company has also incorporated technology from Traceable, an app observability and security company that CEO Jyoti Bansal started. Aligning DevOps and application security more closely is consistent with the broader market trend of mixing runtime visibility with pre-deployment controls, eliminating blind spots across the software development lifecycle.
Traction to Date and the Competitive Landscape
Harness has over 1,000 enterprise customers, including United Airlines, Morningstar, Keller Williams and National Australia Bank.
- Total deployments: 128 million
- Build actions: 81 million
- API calls secured in the last year: over 1.2 trillion
- Cloud spend optimized: almost $2 billion
The market is also fiercely competitive, with plenty of entrenched incumbents and modern cloud-native services. Developer workflows are also fought for by Microsoft’s GitHub, GitLab, Jenkins and CloudBees. Harness differentiates through its knowledge graph, agent-driven automation and governance-first approach, which resonates within organizations in which reliability and auditability are just as important as speed. This also suggests that Harness is not simply a CI/CD tool but touches cost governance and security too.
Global Expansion Strategy and Upcoming Hiring Plans
Based in San Francisco, Harness has over 1,200 employees at its 14 offices. It has about 33 percent of its workforce in India, led by a sizeable engineering hub in Bengaluru and a corporate office in Gurugram. The additional funding will speed up R&D, bring “hundreds” of new engineers to Bengaluru and enhance automated testing, deployment and security in addition to boosting AI accuracy.
On the go-to-market side, the company plans to grow in the US and internationally, focusing on verticals where compliance-heavy software delivery has typically proven resistant to automation.
Why This Funding Round Matters for the Company Today
Generative AI has moved the constraint from writing code to shipping it safely. That shift has created an urgency around systems that can help enforce policies, validate changes with high signal-to-noise testing and programmatically orchestrate rollouts with guardrails — without causing development teams to grind to a halt. If Harness can continue to demonstrate that it can shrink that cycle while also cutting down on incidents and cloud waste, then it becomes a foundational piece in the AI software supply chain.
Outlook for the Business and the Company’s Path to IPO
Its founder Jyoti Bansal, who sold AppDynamics for billions to Cisco, has also made it clear that an IPO is very much part of the playbook when conditions are right. Coupled with new capital, increasing enterprise adoption and a product strategy of automating what is the most expensive part of software delivery, Harness is effectively trying to become one of the platforms of record in the post-code world.
