The GitHub for machine learning
AI Developer Tools
Frameworks, SDKs, hosting and infrastructure for building and running AI-powered software.
180 live tools in AI Developer Tools · ranked by monthly traffic and community votes · dead links removed automatically
Memory · Agents · Studios An AI that remembers and works for you.
Your AI Governance Co-Pilot
Build bigger, better, faster, for less.
Over 5,000 users run confidential compute workloads here
Minutes, not hours
No free plan here
A training API that hands control of model fine-tuning to researchers while someone else deals with the servers and scaling headaches
No free plan exists for Doctor Droid
Microsoft's pay-as-you-go model covers hundreds of AI services
AI-driven incident management platform with Slack integration for automated alerting, response coordination, and postmortem reporting.
The SDK handles on-device AI inference by routing model execution through three distinct hardware backends
Most specs go stale the second code starts flowing
Some features sit in COMING SOON—printable cheat-sheets and team analytics aren't ready yet
Data annotation costs serious money
Application crashes and performance issues cost companies real users — 53% of consumers abandon apps after encountering freezes or errors
Scan credits roll over with SecureSaaS
Debugging web apps with Claude Code
A machine learning engineer prepares a dataset for training a character LoRA and faces 500 images that need detailed captions
TAAFT brings backend infrastructure to Cursor IDE through a visual interface that eliminates the need to code database schemas, authentication systems, or payment logic manually
Cloudir LLM Ops tracks and controls costs for AI agent deployments by monitoring API spending in real time and automatically routing requests to cheaper models when possible
Link shortening gets integrated directly into AI conversations through tny
An AI engineer at a fintech startup builds a customer support chatbot
Model evaluation meets active learning in Encord, a system built to guide AI applications from initial data work through production deployment