How Weco Explores Hundreds of Solutions
Weco autonomously generates, branches, and tests hundreds of candidate solutions - building an evolutionary tree to find the best one. Click any node to inspect examples.
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Our core engine, AIDE, achieved ~4× the medal rate of the next best autonomous agent across 75 Kaggle competitions on OpenAI's MLE‑Bench. Independently validated by researchers at OpenAI, Meta, and Sakana AI.
Benchmark Performance(Medal Rate on MLE-Bench)
Academia and Industry Recognition
Weco's innovative approach is featured in leading research papers and industry publications
Deployable Breakthroughs on Autopilot
Ship speedups overnight
Weco proposes, tests, and iterates on code changes autonomously - wake up to optimized code.
Sweep candidates for pennies
Each candidate costs fractions of a cent. Find the non-obvious wins that manual iteration misses.
Your data never leaves your machine
Eval code runs locally where your data lives. Only metrics and diffs are sent - review the open-source CLI to verify.
Works with any language
Python, C++, Rust, JS - if it prints a metric to stdout, Weco optimizes it.
See every experiment in one tree
Each run produces a searchable tree of candidates. Compare any two nodes side-by-side.
Steer with natural language
Add constraints like "avoid unsafe memory access" or "prioritize readability" to guide the search.
It's as Simple as:
1. Point Weco to your eval
Provide a command that prints your metric value to stdout, which will be used to...
2. Run the Weco optimization
Weco proposes code edits, runs local eval, and evolves solutions based on findings.
3. See and ship breakthroughs
Watch progress locally or in the dashboard and see results before merging the winner.
Trusted by frontier AI labs
Choose Your Path
From open-source experimentation to production-grade optimization - pick the option that fits your needs.
Bring Your Own Keys
Use your OpenAI / Anthropic / custom model keys. Model usage billed directly by your provider.
Weco AIDE ML
- Reference implementation of the AIDE algorithm for experimentation
- Only requires a dataset - auto-detects metrics and optimization direction
- Single-machine experiments - runs fully local
- Reproduce paper results and test new agent architectures
- Ideal for academics and rapid prototyping
Weco Platform
20 credits free (≈ 100 steps)
- Massively upgraded AIDE - production-hardened with advanced capabilities
- Works with your evaluation scripts for complex optimization
- Steer experiments with natural language instructions and code confirmation
- AI-powered analysis to understand experiment trajectory in context
- Hybrid architecture - your code stays local, agent runs in cloud
Both options leverage our breakthrough AIDE algorithm for autonomous code improvement.
Frequently Asked Questions
“So amazing to see something built by this team that's substantially underpinning and influencing OpenAI's agentic roadmap.”
Start Optimizing in Minutes
Point Weco at your eval script, run an optimization, and ship winning code: