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AI-Atlas

AI-Atlas analyzes your public GitHub projects to create a detailed map of your AI skills. It evaluates your work based on implementation, not just imported libraries, and provides a comprehensive profile of your AI capabilities across six domains.

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AI-Atlas screenshot

AI-Atlas is a tool designed to analyze public GitHub projects and map the AI skills demonstrated by your work. It focuses on the actual implementation of AI capabilities rather than merely the libraries used. By examining the code and project structure, AI-Atlas identifies the depth and ownership of your work, mapping it across six AI domains: Machine Learning, Computer Vision, Data Science, NLP & LLMs, AI Agents, and MLOps.

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The platform operates by scanning public repositories, filtering out noise such as forks and empty projects, and then reading the code to understand the actual contributions made. It places demonstrated work across the six domains, giving more weight to deeper projects. The result is a profile that shows the shape of your public AI portfolio, with evidence linked back to the source files.

AI-Atlas offers a free tier where users can map their public AI repositories and view scores and evidence. For more detailed planning, users can purchase planning credits to generate AI improvement roadmaps and project merit scenarios. These credits are one-time purchases and do not expire, allowing users to generate prioritized roadmaps or what-if scenarios for specific rubric dimensions.

The platform emphasizes security by ensuring that code is read but never executed, maintaining the integrity of the evaluation process. AI-Atlas is particularly useful for AI engineers and developers looking to showcase their skills and contributions in a structured and evidence-based manner.

  • CategoryAI Code Review & Testing
  • Pricing ModelFreemium
  • DeploymentCloud
  • PlatformsGitHub

  • Public GitHub project analysis

  • AI skills mapping

  • Six AI domains coverage

  • Evidence-based scoring

  • Free mapping and scores

  • Planning credits for roadmaps

  • Security-focused code reading

  • No subscription model

  1. Discover: Find public repositories

  2. Understand: Analyze code and structure

  3. Map: Place work across AI domains

  4. Explain: Create an AI skills profile

  • Skill Mapping
  • Project Evaluation
  • Roadmap Planning
  • Portfolio Showcase
  • Security Assurance

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