Harness, the AI software delivery platform company, announced a $240 million Series E round. The funding round reportedly includes a $200 million investment led by Goldman Sachs Alternatives as well as a planned $40 million tender offer with contributions made from IVP, Menlo Ventures, and Unusual Ventures. This investment now values Harness at $5.5 billion and reflects the demand for a AI-enabled platform for software delivery.
Although AI is transforming how software is written, that work is said to now represent only the start of the engineering lifecycle.
Most professional teams tend to spend around 30–40% of their time writing and iterating on code; the remaining 60–70% goes to the “outer loop” — testing, deployments, security, compliance, and optimization.
These workflows are said to be interconnected and mostly manual, creating friction that “slows down processes.”
Harness is said to be bringing AI and automation to this outer loop, turning the time-consuming “parts of software delivery into more intelligent, frictionless processes.”
AI is amplifying the pressure considerably.
Code volume is now said to be accelerating and every line must “still be tested, secured, deployed, and maintained.”
The rise of AI-generated code is now said to be “widening the gap between development and the reliable delivery of software.”
Organizations need intelligence and automation that is able to effectively manage the after-code lifecycle — and Harness claims it now “provides the platform that brings these different AI capabilities together.”
The proceeds from the investment round will aim to help accelerate the evolution of Harness AI, a “unified system purpose-built for everything after code.”
Harness AI is designed to eliminate the “downstream bottlenecks that slow down engineering velocity.”
By combining specialized AI agents, organizational context, and orchestration, the platform “turns software delivery workflows into an intelligent system that learns, adapts, and acts on behalf of engineering teams.”
Harness AI is built with foundational layers that “bring intelligent automation” to the software development lifecycle:
AI Agents purpose-built for software delivery: A library of focused agents that perform delivery, testing, verification, security, governance, and operational tasks — “removing the manual coordination traditionally required across teams and tools.”
The Software Delivery Knowledge Graph: A unified context model mapping “code changes, services, deployments, tests, environments, incidents, policies, and cost signals.”
This layer makes AI precise and aligned “to each customer’s architecture and workflows.”
Enterprise-grade orchestration engine: A reliable execution engine that transforms AI-driven insight into “consistent automation across pipelines and environments, ensuring decisions are evaluated and implemented safely and predictably.”
With organization-specific context, every action taken by Harness AI is precise and “aligned to each customer’s architecture and workflows.”
Issues are identified earlier, “evaluated with full context, and resolved before they reach production.”
According to the announcement, teams ship faster, “not because they accept more risk, but because the platform absorbs the complexity on their behalf.”
This next phase of software delivery is taking shape across Harness’s customer base, reflected in the global momentum Harness has built:
- ARR Growth: On track to exceed $250M ARR in 2025, with 50%+ YoY growth.
- Scale: Powered 128M deployments, 81M builds, 1.2T API calls protected, and $1.9B in cloud spend optimization for customers over the last 12 months.
- Adoption: Trusted by 1,000+ enterprise engineering teams across North America, EMEA, and APAC.
- Expansion: Grown to a 1,200+ employee team across 14 offices worldwide.
Harness will use the capital injection to enable platform updates, expand its global footprint, and advance its vision for a world where “the process of getting code to production is automated and governed by design.”
Harness is the AI DevOps Platform company, “enabling engineering teams to build, test, and deliver software.”
Powered by Harness AI and the Software Delivery Knowledge Graph, the platform reportedly brings “intelligent automation to the software delivery lifecycle after code.”