Peeling Back the
Layers of
Generative AI
We are building the world's first on-demand, no code tool
for benchmarking and running evaluations
against foundational models
Preview

Atlas Beta Release

We are opening our flagship benchmarking and testing product, Atlas, for private betas. If you are a data scientist, engineer, or founder struggling with selecting the right generative AI model for your use-cases, we would love to talk to you.

Book a Demo

Generative AI has a testing problem.

Advancements are being made at breakneck speed. Indeed, every week seems to be a year when it comes to the proliferation of new models or the release of a new technical paradigm. However, there is no reliable method to ascertain the actual ability of these models over time. This is where LayerLens comes in.

Easy Evaluation for AI Models

Our goal is to provide businesses and developers with an easy, digestible way to assess AI model performance for industry-specific use-cases.

In-depth Analysis

Evaluations are run on-demand, requiring no manual code execution or library management. All evaluation results for public models are displayed in a comprehensive leaderboard.

Wide Coverage

We currently support over 200 generative AI models and over 50 evaluation datasets, across numerous categories and use-cases.

Use-Case Specific Evals

We plan on creating and supporting new evals for practical, everyday tasks. Rather than relying on academic-intensive datasets, you will be able to leverage custom datasets focused on use-cases such as SQL DB management to spreadsheet analysis.

Enterprise Focus

We are currently working on an enterprise-specific experience, that will allow for propiterary datasets and private models to be seamlessly integrated within the LayerLens platform.

Call to Innovators

If you are passionate about jailbreaking, datasets, and distributed computing, and want to join a team of skilled engineers, reach out! Alternatively, if you are building at the edge of AI and want to integrate evals into your application, we would love to talk to you.