AI & machine learning

AI agents: run long-lived sessions, tasks, files, memory and channels over HTTP

Generation and knowledge graphs: chat, text completion, file uploads, PDF parsing and application jobs

Agent orchestration: run agent sessions, projects, PRs, reviews and automations locally

AI models: generate text and speech, transcribe audio, embed text, and manage files and batches

AI model proxies (OpenAI, Anthropic), file storage, email auth and run management in one gateway

Browser sessions, web scraping and crawling, and cloud sandboxes for running AI agent tasks

ML training pipelines: create and track batches, manage models, evals, review queues and billing spend

Browser automation: cloud browser sessions, page scraping, web AI agents and credential vaults

AI chat, sessions, files, images, audio, video and agents: send messages, generate media and run agents

Language, image, video and speech generation: chat, embeddings, batches, transcription and TTS

AI model gateway: chat, embeddings, images, audio, video, batches and files via OpenAI- and Anthropic-style endpoints

AI image, video, 3D and audio generation: create media, upload assets, train styles, run node apps

Machine learning: manage experiments, models, deployments, aliases, batch and realtime predictions

LLM gateway: chat and responses inference, models, routing keys, usage and bridges

AI agents: configure conversational agents, channels, conversations, prompts and tools for voice and SMS

GenAI platform: build agents, prompts and knowledge bases, run evals, and query logs and traces

Hosted AI agents: deploy agents, manage sandboxes, networks, webhooks, triggers and billing

Cloud computers for AI agents: run shells, screens, apps, deploys and agent chats

AI agent society: post, trade offers and listings, bind keys, and verify signed ledger checkpoints

Generative media and chat APIs: images, video, audio, models, assets and recipes

AI agents: build, trigger and test agents, plus manage runs, triggers, skills and owners

Cloud coding agents: open sessions on your repositories, stream their work, manage secrets, skills and automations

Multi-agent orchestration: distribute tasks, manage agents, sessions, skills, schedules and MCP servers

AI models: generate text, speech and embeddings, manage files, batches and fine-tuning jobs