Inefficient code quietly drains gross margin, compresses runway, and makes scale more expensive than it needs to be. A Codeflash Optimization Engagement finds that waste across your production system and ships the fixes. Every change created by our agent is crafted & reviewed by our senior performance engineers, proven correct, and delivered as a PR. ROI guaranteed before you commit.
Every dollar you over-spend on cloud is a dollar not in product, headcount, or runway.
Gross margin is under pressure. You know the spend is higher than it should be, but quantifying the opportunity and capturing it without disrupting the team hasn't happened yet.
We've found 118 functions up to 446× slower than necessary in two AI-written PRs. The velocity is real. So is the waste it introduces.
Unit economics are slipping as you grow. A 90% infra cut doesn't just lower the bill. It changes what scale looks like and how long your runway lasts.
The engagement is scoped, time-bounded, and ends with working code on your repo. Not a PDF report.
We agree on a target: cost, p99 latency, GPU utilization, cold start, or throughput. We reproduce your baseline on a representative workload so everything is measured before we touch a line of code.
codeflash-agent profiles your codebase, generates optimization candidates, and benchmarks each one in our sandboxed environment. It finds global patterns across files and across layers that a human working function-by-function would miss.
A senior Codeflash performance engineer reviews every optimization. Fragile ones are rejected. Anything that doesn't meet our quality bar never reaches your repo. This is not AI output with a rubber stamp on it.
Each PR arrives with before/after benchmark numbers and reviewer rationale. Your team reviews and merges. We never push directly to main. Your engineers stay in control.
A human perf engineer works file by file. codeflash-agent has your entire codebase in view at once. It finds six-step flows that can become three-step flows. It sees the O(N²) scan nested two abstractions deep. It catches the 24 MB memory creep hiding inside baseline noise.
It runs 24/7, in parallel, in our sandbox. Your engineers don't drive it. They review the output. Your team's job goes from doing the optimization work to approving it.
"Having Codeflash run the agent makes more sense than asking our engineers, who are focused on product and features, to develop and run that process themselves."
Claude, Cursor, and Codex operate at the point of authorship. The waste already in production, and the waste being added at speed by those same tools, requires a different approach.
| Claude · Cursor · Codex | Codeflash Engagement | |
|---|---|---|
| Cloud bill impact | None. No visibility into production cost | → 40–90% infra cost reduction, measured |
| Where it looks | The file currently open | → Your entire production system, layer by layer |
| Proof the change works | No before/after benchmark | → Every PR has measured speedup and regression tests |
| Your team's time cost | Engineers must prompt, review, and validate | → You review PRs. We do everything else |
| ROI before you pay | Unknown | → Savings opportunity quantified in the diagnostic |
Here is exactly what you get at the end of an engagement.
We reproduce your baseline on your actual workload before touching a line. No guesswork. The improvement is measured from a real number, not a projection.
Each PR includes before/after benchmark numbers, correctness verification across your test suite, and a plain-English rationale from the reviewing engineer. Your team reviews and merges at their pace.
A Codeflash performance engineer reviews every candidate before it reaches your repo. Fragile, risky, or marginal optimizations are rejected. You only see the ones we'd stake our reputation on.
Bottlenecks found, methodology, PRs shipped, before/after metrics, and a scope recommendation for the next phase if applicable. The report is yours to keep.
The agent runs in our sandboxed environment. We never touch your production systems. Read-only GitHub access, scoped to the agreed repos, time-limited. SOC 2 Type 2 audited.
At the end of the engagement, the same agent can watch every new PR going forward, catching regressions before they compound. The bill stays down, not just this quarter.
Every engagement starts with a paid diagnostic. In three weeks, we profile your system, identify your top bottlenecks, and quantify the annual dollar opportunity. That diagnostic is the decision point, not a down payment on a foregone conclusion.
If we don't identify at least 5× the diagnostic fee in annualized savings, the diagnostic is on us. We've never triggered that clause. But it's there because we mean it.
Commercial structure (scoped fixed fee or shared-upside) is agreed before work begins.
Chief Architect at Unstructured, after seven weeks.
"We knew we could do better, but we didn't have the bandwidth."
"It wasn't just tweaks to existing functions. Codeflash understood the abstractions. If a process had six steps, it would recognize that two or three were unnecessary and replace the flow with a better one."
"A PR comes in, we measure RSS before and after on a running system, and the improvement is 2× or 3×. Real demonstrable progress, not theoretical."
Most optimization wins decay inside a year because new code arrives faster than anyone can optimize it. We close that loop.
codeflash-agent explores your existing codebase. Our engineers review and ship optimizations. You see the bill bend in weeks.
Start an engagement →The same agent stays on, watching every new PR. Regressions are caught where they're introduced, before they compound. Works with GitHub, Claude Code, Cursor, and Codex.
See Continuous Optimization →The diagnostic takes 2–3 weeks. A full engagement typically runs 4–12 weeks depending on codebase size and scope. We agree on a timeline before we start.
One or more repos, a benchmark or a profile (if you don't have a benchmark, we can write one), a defined objective, and time to review PRs. We don't need production access and we don't need to be onboarded to your infrastructure. Your team reviews PRs; we drive everything else.
AI coding tools optimize within a function, at the point of authorship. codeflash-agent profiles your running system, identifies the real bottlenecks, and rewrites across layers. Then every change is benchmarked and correctness-verified before a Codeflash engineer reviews it. The output is a PR with measured proof, not a suggestion.
Minimally. We don't need pairing sessions or access walkthroughs. Your team's job is to review PRs, the same way they review any other change. The agent explores autonomously in our sandbox.
The diagnostic is the checkpoint. If we can't identify savings that clearly exceed the diagnostic fee × 5, we tell you and the diagnostic is refunded. We've never triggered that clause, but it's there.
Never. Not ours, not any third party's. That's in our Trust Center and our SOC 2 Type 2 audit.
Yes. Deployment model (SaaS, your cloud, or on-prem) is agreed during scoping. Same agent, same process.
Python, Java, JavaScript, TypeScript, Go, and more. ML stacks including PyTorch, JAX, vLLM, HF Diffusers, YOLO, and spaCy. If you're not sure, tell us your stack and we'll give you an honest answer.
We'll profile your system, identify the top bottlenecks, and tell you what the savings opportunity looks like before you commit to anything.