“coding”

Open-source infrastructure that runs AI-generated code in isolated cloud sandboxes.

Code execution API that lets LLM-generated code run in isolation and returns its output.

Context and memory layer that syncs project decisions and rules selectively across coding agents and teammates.

Fine-grained authorization for apps, APIs and AI agents, with policy as code and an MCP gateway

Open-source platform for code-first API integrations, auth and MCP tools for products and agents

Open-source, MIT-licensed platform for observing production AI agents and turning failures into tracked signals

Launch computers for agents, code sandboxes and apps on hardware-virtualized Fly Machines.

Open-source tool that converts PDFs, images and Office files to markdown, JSON, chunks and HTML.

Open-source orchestration platform for data, AI and infrastructure workflows, defined in YAML.

Isolated Linux devboxes for running AI agents and their code, with snapshots and reusable blueprints.

Model router that predicts which LLM to call for each request, aimed at cutting coding-agent costs.

Database for unstructured and multimodal data that powers AI apps and agents, with MCP support.

Durable workflows and queues that run on Postgres, for backends and AI agents.

Browser infrastructure for AI agents: stealth cloud browsers, an open-source Playwright-based framework and deployable functions.

Observability and dev-tool platform for building, evaluating and monitoring AI agents

AI gateway giving one API to 250+ models, with observability, guardrails and prompt management.

Real-time AI infrastructure for deploying voice agents, video models, LLMs and other AI workloads, with autoscaling.

Cloud browsers and hosted browser agents that connect over CDP and get past bot checks.

Governed platform for every agent, model and tool a company runs, deployable in its own cloud.

Platform for agent observability and evals: trace agents, score outputs and find patterns in production