Harness closed a $240 million Series E financing round at a $5.5 billion valuation, led by Goldman Sachs Alternatives, targeting what CEO Jyoti Bansal calls “the biggest bottleneck in software engineering” — everything that happens after code is written.

The funding addresses a fundamental infrastructure crisis emerging as AI accelerates development velocity. While AI tools enable developers to write code several times faster, the downstream processes of testing, securing, deploying, and governing that code remain largely manual, creating an exponentially widening delivery gap that threatens to paralyze enterprise software operations.

Engineers at modern software companies spend up to 50% of their time debugging production failures instead of building new features. Deductive AI, founded by Databricks and ThoughtSpot veterans, emerged from stealth this week with $7.5 million in seed funding to deploy AI SRE agents that cut incident resolution time by up to 90%.

The timing reflects a brewing crisis in software reliability: as AI coding assistants accelerate development velocity, they’re simultaneously creating more complex, harder-to-debug systems. The result is what Deductive calls a “debugging crisis” where world-class engineers spend half their time firefighting instead of innovating.

System Initiative today unveiled what it claims is the world’s first AI-native infrastructure automation platform, enabling DevOps teams to collaborate with autonomous agents that understand, propose, and execute infrastructure changes through high-fidelity digital twins.

The platform addresses a critical enterprise bottleneck: according to theCUBE Research, 65% of organizations cite complexity as a top-three challenge in cloud infrastructure management, while 72% lack real-time cost visibility—constraints that effectively block automation adoption at scale. System Initiative’s approach moves beyond traditional Infrastructure-as-Code tools by pairing AI agents with complete digital replicas of production environments, enabling natural language interaction with infrastructure that can safely execute validated changes.

SRE.ai secured $7.2 million in seed funding led by Salesforce Ventures to deploy AI agents that autonomously manage enterprise software deployment workflows, addressing the bottleneck where teams spend weeks stitching together testing environments and debugging deployment pipelines across multiple cloud platforms.

The funding validates a critical enterprise infrastructure challenge: while AI has transformed how code is written, the deployment and operations side remains largely manual, creating delays that can stretch simple releases into multi-week ordeals involving multiple teams, complex toolchains, and fragmented monitoring across AWS, Google Cloud, and enterprise SaaS platforms.