Adaptive6 debuts code‑centric platform to detect and auto‑remediate hidden cloud waste, raising $44M

Adaptive6 has emerged with funding and a clear thesis: cloud cost overruns are not merely accounting problems but faults rooted in code, configuration, and architecture. The company’s platform scans multi‑cloud estates without agents, links wasteful resources to the exact code paths and authors, and injects remediation into developer tools so fixes happen where the change originated. That approach flips ownership away from centralized finance teams and toward engineering, arguing that visibility dashboards alone leave the real problem unaddressed. Technically, the system ingests telemetry from major cloud providers and PaaS layers, analyzes runtime and provisioning patterns, and evaluates architectural choices that standard cost suites overlook. Adaptive6 emphasizes scenarios where inefficiency is subtle — for example, mismatched provisioned throughput for large model endpoints or legacy runtime versions that inflate execution time — and generates targeted recommendations or automated patches. The startup says it augments generative techniques with expert research to avoid the brittle or costly output that off‑the‑shelf code agents can produce. Early deployments at large customers reportedly deliver mid‑teens to mid‑thirties percent reductions in cloud spend, and the platform includes preventive checks that run in CI/CD to stop costly designs before they reach production. By treating waste like a security vulnerability, Adaptive6 can trace, alert, and remediate in a way that maps to existing developer workflows such as ticketing and pull requests. The company bets this model will scale in complex enterprises where decentralized teams create the bulk of hidden inefficiencies. If successful, the shift could change how organizations measure cloud economics — moving from retrospective dashboards to proactive, code‑level governance. That transition would also force cultural and process changes: developers must accept cost signal feedback and remediate issues as part of delivery, while FinOps roles evolve into policy and enforcement partners. The broader implication is a tighter coupling between software engineering practices and infrastructure economics, particularly as AI workloads make cost behavior less predictable. Adaptive6’s market entry comes as public cloud spending continues to accelerate, so tools that can convert visibility into automated corrective action may become a practical necessity rather than a nicety.