Isyouragentactuallygettingbetteratcoding?
Fresh Evals generates fresh, private, human-verified software engineering evals from the largest categorized repository graph available: 177 million repositories. Your models have never seen these tasks, so you find out how your agent really performs.
- Reproducible
- Dockerized
- Hidden tests
- Provenance tracked
- Benchmark ready
Publicbenchmarksstoppedtellingyouthetruth.
Every frontier team leans on benchmarks like SWE-bench to answer one question: is our agent getting better? The trouble is that those benchmarks were never built for the agents you ship today.
Public
With public datasets like SWE-bench, your competitors train and tune on the exact same set.
Static
Public benchmarks stay frozen, serving the same tasks week after week.
Contaminated
Public benchmarks leak into pretraining data a little more every release.
Python-centric
Existing benchmarks are mostly Python, blind to your real stack.
Not customized
Off-the-shelf benchmarks are generic and never touch your domain.
Limited
Public benchmarks are issue-to-patch, and little else.
Abenchmarkthatregeneratesfasterthanmodelscanmemorizeit.
We generate fresh, private, human-verified evaluation tasks directly from the open-source software ecosystem. Every task is reproducible, Dockerized, hidden, human reviewed, provenance tracked, and benchmark ready, on a schedule that never goes stale.
177M categorized repositories
Deterministic filters + candidate mining
AI synthesis into reproducible tasks
Dockerized environment + hidden tests
Human review and sign-off
Your private, benchmark-ready suite
categorized repositories in our graph.
Nobody hand-builds a benchmark from 177 million repos. That search universe is the moat, and everything fresh, private, and custom flows from it. A benchmark doesn't need millions of tasks to be great. The advantage is in how much we get to choose from.
Wecompeteonevaluationquality.
Not prettier dashboards. Every advantage below comes from one place: the largest categorized software repository graph available.
Fresh
Post-cutoff by design.
New benchmark tasks every month, drawn from code that did not exist at training time. Models literally could not have memorized the answer.
Private
Your holdout, nobody else's.
Private holdouts, hidden tests, and private Docker images per customer. Your benchmark is yours alone, never published and never shared.
Massive search space
177M repositories deep.
We don't pick from 500 verified tasks. We search across the entire categorized open-source ecosystem to surface exactly the right ones.
Custom
Built for your agent.
Java agents? Generate Java tasks. React agents? React tasks. Enterprise backends? Exactly those. No public benchmark can target like this.
Human verified
AI-first, human-certified.
AI generates and filters at scale. Humans approve every task before it ships. The pipeline is automated; the quality is signed off by people.
Production realism
Real maintenance work.
Bug fixes, dependency upgrades, migrations, CI failures, code review, security fixes, refactors, and vague customer reports. Not just issue to patch.
Theworkyouragentactuallyfaces.
Real engineering is not a tidy issue-to-patch loop. Our tasks span the full surface area of software maintenance, so your scores reflect production reality instead of a benchmark's convenient subset.
Ascoreisanumber.Wegiveyouareason.
Knowing you scored 63% tells you nothing about what to fix next. We tell you exactly where and why your agent breaks down.
“You scored 63%.”
Accurate, and completely unactionable. Now what?
“You fail on dependency upgrades because your localization breaks before planning.”
A specific failure mode you can route, reproduce, and fix this week.
Findoutwhereyourcodingagentreallystands.
Tell us the stack your agent targets and what you need to measure. We'll scope a fresh, private, human-verified benchmark built for exactly your use case.
- Post-cutoff tasks your model has never seen
- Private holdouts and hidden tests, yours alone
- Custom to your language, framework, and domain
- Actionable failure analytics, not just a score