A key question at this year’s FinOpsX conference was: what does “AI for FinOps” really mean? Today, we’re answering that with the general availability of AutoFix pull requests for GitHub.
Infracost doesn’t just prevent new cost issues anymore, it now opens AI-powered pull requests to fix existing ones. Engineers can remediate issues 10x faster and at scale, with validated code fixes that avoid the risks of LLM hallucinations.
For enterprises, this means cost optimization finally scales: engineers take action without extra meetings or manual coordination, and FinOps leaders can track progress quarter over quarter. AutoFix turns AI for FinOps from a buzzword into practical, developer-first solutions already used at Fortune 100 enterprises.
Skip Jira tickets and meetings with AutoFix pull requests
Cloud cost issues pile up quickly in large enterprises; tens of thousands of issues across thousands of code repos. FinOps teams try to surface them in Jira tickets or planning meetings, but those get delayed or deprioritized. Meanwhile, developers rarely go looking for cost issues buried in AWS or Azure consoles or spreadsheets. The result: problems sit unresolved for many quarters, if they get fixed at all.
AI sounded like the answer, but we quickly discovered the limits. LLMs don’t understand an organization’s priorities, and they hallucinate. Bad or irrelevant code fixes waste engineers’ time and destroy trust. The right fix might involve updating a module or adjusting variables, and engineers reviewing the pull request need context on deployment details (e.g., does the VM require a reboot when changing the volume type?) and the risks of the change (e.g., applying a storage lifecycle policy deletes old data). What’s needed is action at scale on the highest-priority campaigns, with context so engineers are fully informed to review and approve each change.
That’s what AutoFix delivers. Infracost now goes beyond detecting new cost issues when engineers are making changes; it proactively opens pull requests to fix existing issues across your codebase. Engineers review and merge, just like they do with security fixes. The results speak for themselves: one customer fixed 300 issues in just 2 weeks — 10x faster than before!
Why this matters
- Actionable fixes at scale: Cloud infrastructure is decentralized, so fixing cost issues is a distributed problem. FinOps initiatives—like adopting Graviton—require engineers across many repos to take action to realize savings. Developers don’t chase Jira tickets or sit in monthly FinOps meetings. AutoFix surfaces actionable opportunities directly in GitHub as new pull requests, putting the data where engineers already work and making distributed action simple and scalable.
- Speed without bottlenecks: Get more savings applied faster because AutoFix eliminates the back-and-forth of two engineers coordinating. Normally, one engineer has to open a PR and another has to review it; multiplying the effort and slowing everything down. With AutoFix, the Infracost bot opens the PRs so engineers can simply review and merge; no bottlenecks, no delays. This is the same model security teams rely on to drive adoption: by lowering the effort required, you get dramatically more action.
How it works
- FinOps teams create a campaign to highlight which policies matter most this quarter; whether that’s adopting Graviton, or tightening log retention. Infracost then automatically opens PRs with actionable code fixes, intelligently paced so engineers aren’t overwhelmed, while tracking progress across repos. And if you’re using the standard GitHub
CODEOWNERSfile, AutoFix PRs are automatically assigned to the right engineers or teams so they’re notified immediately and can take action without extra coordination. - AutoFix combines context from our static analysis engine (the Infracost CLI), and customer-specific policies and price books to generate actionable code fixes, using AI to power the code generation. You can also customize the prompt passed to the LLM for each policy. For example, you can instruct it to set log retention to 30 days when opening pull requests to fix AWS CloudWatch issues.
- Our static analysis engine validates each fix, ensuring it resolves the issue without introducing new costs or breaking changes. This reliability is essential for enterprise AI adoption. Enterprises don’t just want LLMs that may hallucinate; they need confidence that solutions are safe, predictable, and won’t waste engineering time.
Conclusion
AI for FinOps isn’t about flashy buzzwords; it’s about making action possible at scale. With AutoFix, engineers finally get validated, AI-powered pull requests that make fixing issues 10x faster and easier, directly in their workflow.
👉 Log in to Infracost Cloud and start a free 2-week trial to test AutoFix pull requests! If you prefer a live demo, book one here.
