# What is Portex?

PortexAI builds evaluations ("evals") for state-of-the-art AI models and agents. Evals have become a bedrock of the AI ecosystem as they are increasingly doing double duty: they both contextualize model performance in benchmarks and provide reward signals for post-training and reinforcement learning.

Portex Evals are expert-authored, domain-specific evaluation datasets and grading rubrics designed to measure frontier and economically-relevant work by AI models. Each eval is a set of procedural tasks (with optional reference files) plus a private answer key and explicit rubric used by our AsymmetryZero LLM-jury protocol or lexical judge to produce standardized scores and reports.

The [PortexAI Datalab](https://datalab.portexai.com) is where experts design, publish, and commercialize evals and accompanying datasets, and where model builders can license task bundles or evaluate their model's responses.

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These docs cover how to create evals, run them, and use the Datalab as either an expert or a model builder.

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New here? Start with [Creating an Account](https://docs.portexai.com/portex-docs/getting-started/creating-an-account) or read [How Evals Work](https://docs.portexai.com/portex-docs/core-concepts/how-evals-work) for a conceptual overview.
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