AI tools for Machine Learning Engineers

Cheap GPUs on demand

Run AI code without infrastructure

Cheap AI inference

Vector database for AI applications

Models to production fast

Vectors at scale

Scale AI effortlessly

The GitHub for machine learning

Minutes, not hours

Enterprise teams running open-source AI models in production get infrastructure that handles the heavy lifting without MLOps expertise

A training API that hands control of model fine-tuning to researchers while someone else deals with the servers and scaling headaches

Hybrid autoregressive diffusion image generator

Data annotation costs serious money

A machine learning engineer prepares a dataset for training a character LoRA and faces 500 images that need detailed captions

Model evaluation meets active learning in Encord, a system built to guide AI applications from initial data work through production deployment

Cerebrium is a serverless GPU platform for running AI workloads in production.

Roboflow is a computer vision platform that turns images, videos and camera streams into structured data.

Portkey puts a single API in front of more than 1,600 language models and wraps it with the controls a production AI team needs.

Langfuse is an open-source platform for observability and evaluation of AI agents and LLM applications.

Beam is a cloud runtime for AI workloads that offers serverless GPUs, task queues and sandboxes through a Python, TypeScript and Go SDK.

Arize Phoenix is an open-source platform for AI observability and evaluation, built by Arize.

LangGraph is an open-source agent runtime and low-level orchestration framework for building AI agents that behave reliably on complex tasks.

Weights & Biases is an AI developer platform for tracking, evaluating and debugging machine learning models and LLM applications.

TRL, short for Transformers Reinforcement Learning, is a Hugging Face library for post-training transformer language models.