Search and filter curated AI tools. Find the right tool for your task.
Each tool shows verification (how recently we checked the link), link health (whether the URL works), and trust (0–1, combining both). Verified + HTTPS = highest trust. Pending = not yet checked. Stale = last check was 1–3 days ago. Failed = over 3 days.
Feature store and ML data platform for managing machine learning infrastructure at scale. Integrates feature engineering with ML operations. Manages real-time and batch features. Governance and data quality monitoring. Model training and serving capabilities. Integrates with data pipelines and warehouses. Used by enterprises with complex ML infrastructure. Combines feature store with broader ML platform. Commercial offering with open source components.
Cloud GPU and AI computing service providing on-demand access to powerful AI hardware for training deep learning models. High-end GPUs including A100, H100, and other advanced hardware. No long-term contracts required. Simple pay-as-you-go pricing. Easy integration with ML frameworks. Used by researchers and companies training large models. Alternative to building local GPU infrastructure. Growing service for serious ML work.
Cloud machine learning platform providing GPU infrastructure and tools for model training and deployment. Managed Jupyter notebooks in the cloud. Easy access to GPUs without managing servers. Workflows for training and serving models. Model management and deployment. Team collaboration features. Simple pricing for cloud GPU access. Alternative to managing local GPU hardware. Growing adoption among ML practitioners.
AI risk management platform that tests and monitors AI systems to identify vulnerabilities before and after deployment. Performs comprehensive testing of models for robustness, adversarial attacks, and edge cases. Continuous monitoring in production catches model degradation and issues. Provides detailed reports on model risks. Essential for high-stakes applications. Used by enterprises deploying critical AI systems. Helps prevent costly model failures.
AWS integrated development environment for machine learning providing complete ML development experience. Managed Jupyter notebooks for experimentation. AutoML for automatic model building. Built-in algorithms and frameworks. Model training at scale with managed compute. Model deployment and serving infrastructure. Feature store integration. Monitoring and governance. Tightly integrated with AWS ecosystem. Growing adoption on AWS.
Feature management platform centralizing feature engineering for machine learning systems. Creates a single source of truth for ML features. Supports both offline training features and online serving features. Real-time feature computation for low-latency predictions. Governance and monitoring for feature quality. Scales to enterprise feature demands. Reduces duplication between teams. Used by companies managing complex feature infrastructure.
Google Cloud end-to-end machine learning platform for training and deploying ML models at scale. Provides notebooks and IDEs for development. AutoML for automated model training. Managed model serving with prediction infrastructure. Includes pre-built models and APIs. Integrates with Google BigQuery for data. Monitoring and governance features. Leverages Google's ML expertise. Growing alternative to AWS and Azure.
API design and documentation tool with AI-powered auto-generation.
Open source API client for testing REST and GraphQL APIs with local-first design philosophy. Lightweight alternative to Postman focusing on simplicity and privacy. Store API collections in version control instead of cloud. No sign-up required. Works offline. Plain text collection format for easy version control. Includes environment management and scripting. Active development and growing community. Free and open source.
Automated API documentation platform that keeps your documentation in sync with API changes. Generates beautiful documentation from OpenAPI specifications. Change management features notify users of API updates. Collaboration and version history. Integrates with GitHub for automatic updates on commits. Publishes documentation automatically. Great for teams that update APIs frequently. Commercial service. Growing adoption among API-first companies.
Lightweight documentation site generator with AI-powered search.
Facebook's open-source documentation framework with AI search plugins.
API documentation and SDK generation platform with an IDL-based approach. Define your API once in Fern IDL and generate documentation and SDKs automatically. Generates docs and SDKs in multiple languages. Supports OpenAPI integration. Beautiful generated documentation. Growing ecosystem of integrations. Removes duplication between docs and code. Open source with commercial support available.
Headless documentation framework built for Next.js developers who want full customization control. Provides the documentation infrastructure while you maintain complete control over design and components. Flexible component system lets you build unique documentation experiences. Supports Markdown and MDX for rich content. Works great for teams with custom design requirements. Open source. Perfect when you want documentation features with custom branding.
User-friendly command-line HTTP client that makes API requests simple and intuitive. Request syntax is more readable than curl. Includes syntax highlighting, formatted output, and excellent error messages. Supports authentication and sessions. Great for API testing from the terminal. Works great in scripts and automation. Both CLI and browser-based versions available. Open source and growing adoption. Perfect for developers who prefer command-line tools.
Markdown extension framework from Stripe for creating content-rich documentation and educational sites. Extends Markdown with custom components and validation. Catches content errors automatically. Syntax for embedding interactive components in Markdown. Works great for documentation that needs custom formatting. Growing adoption by major companies. Flexible approach to content management. Open source and actively developed.
Open source mock API server tool for creating and running mock APIs locally for testing and development. Create mock endpoints without writing backend code. Test frontend code against realistic API responses. Share mock configurations with team members. Built-in data generation for realistic responses. Simple UI for defining mock endpoints. Great for frontend and backend teams working in parallel. Desktop and CLI versions. Free and open source.
Next.js documentation framework with AI-powered search and navigation.
API documentation platform with developer portals and API governance.
Modern API documentation platform supporting both OpenAPI and AsyncAPI specifications. Provides interactive API exploration and testing directly in the documentation. Beautiful responsive design for all devices. Includes authentication support for realistic testing. One-click request examples and code snippets. Deploy standalone or embed in your site. Growing adoption as a Redoc alternative. Open source with commercial offering.
