AI & machine learning

LLM gateway: route chat and embeddings calls, manage API keys, budgets, usage and traces

Multi-capability AI: run generation and voice jobs, manage model adapters and LoRAs, quote charges, track jobs

AI model gateway: chat and messages endpoints, billing via PayPal, Paddle and Creem, referrals

AI generation: create images, video, 3D models and audio, plus enhance and manage assets

Alignment verification for AI agents: manifests, drift alerts, containment, attestations and trust scores

LLM app platform: build and evaluate applications, with testsets, traces, workflows and API keys

Browser automation: run AI agents and tasks, manage runs, credentials, browser sessions and profiles

Data annotation: create projects, label tasks, review annotations, manage storage and ML backends

Model training: run training jobs, store trajectories, deploy models and call chat completions

AI game asset creation: generate images, video, audio and 3D with models, reference sets and training

LLM inference, realtime audio, fine-tuning, evals and dedicated model deployments via one Bearer-token API

AI agent platform: manage agents, workflows, dashboards, secrets, sandboxes and inference providers

Agent orchestration: distribute tasks, route agent messages, and manage sessions, skills and MCP servers

Machine learning predictions: retrieve predicted values, Shapley explanations, source data and related jobs

Agents and skills: manage agents, chats, folder syncs, skill catalogs, billing usage and integration access

Local AI: run LLMs, speech-to-text, text-to-speech, RAG search and cloud API proxying on localhost

Generative AI: run image generations, manage projects, assets, library folders and LoRA training

Local agent sessions, projects, automations, code reviews and pull-request actions for orchestration

AI agent platform: deploy and run agents, manage nodes, licenses, billing and secret keys

AI assistant platform: chats, assistants, files, SharePoint and MS Office integrations, and share grants

Digital twins: model objects, search and link data, run agents, workflows and syncs, track AI costs

Agents: start sessions, stream events, read transcripts and artifacts, manage secrets and keys

Agent environments: manage tasks, tasksets, rollouts, builds, traces, models and QA checks

AI gateway: proxy LLM requests, manage API keys, limits, balances and usage analytics