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| title: README | |
| emoji: ๐ | |
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| colorTo: green | |
| sdk: static | |
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| short_description: Clean feedback and promotion gates for AI agents. | |
| # Verifiable Labs | |
| Verifiable Labs builds clean feedback and promotion gates for increasingly general AI agents. | |
| We develop infrastructure for evaluating agent improvements, checking whether those improvements transfer to unseen/OOD/adversarial situations, and producing synthetic/redacted evidence artifacts for promotion decisions. | |
| ## Public resources | |
| - GitHub: https://github.com/verifiablelabs | |
| - PyPI: https://pypi.org/project/vlabs-sdk/0.0.2/ | |
| - Install: `pip install "vlabs-sdk==0.0.2"` | |
| - Dataset: https://huggingface.co/datasets/verifiablelabs/vlabs-clean-gate-evidence | |
| - W&B: https://wandb.ai/verifiable-labs/clean-generalization-gate | |
| ## Evidence policy | |
| Public evidence is synthetic/redacted and is not a training dataset. | |
| It does not include customer data, hidden evals, gold answers, raw traces, private traps, private engine internals, secrets, or provider keys. | |
| ## Formal scope | |
| Selected mathematical properties behind the contamination-resistant promotion gate are machine-verified in Lean 4. The implementation is property-tested against the formal specification. | |