Embeddable office SDK that unifies spreadsheets, docs, slides, canvases and relational tables in one runtime so humans and AI agents can inspect, edit, verify, and collaborate on the same files. Provides programmatic editing APIs, isolated agent worktrees, a formula engine and a headless Node.js runtime for agent workflows.
A statically typed, parallel programming language that prevents AI-introduced bugs by making correctness claims (laws) require machine-checked proofs. Compiles to native code and targets CPU/GPU parallelism with a fast proof checker.
Provides a Python and TypeScript SDK to build and run production AI agent harnesses — the agent loop plus tools, memory, sessions, context management and lifecycle controls — with model portability and built-in observability.
Compresses tool outputs, logs, files and RAG chunks locally before they reach the LLM to reduce token usage while caching originals for on-demand retrieval. Provides proxy/library/wrap modes, JSON- and code-aware compressors, and reversible compression.
Runs autonomous AI agents in isolated containers with declarative YAML policies that enforce filesystem, network, process, and inference controls. Provides credential providers, inference routing, hot-reloadable network/policy updates, and formal verification of policy changes for auditable agent execution.
Runs and manages persistent teams of coding agents (Claude Code, Codex, Pi) locally — boots named seats from a YAML topology and provides a daemon, CLI and TUI to monitor, snapshot, evolve and coordinate agent workspaces and terminals.
Provides a self‑hosted OpenAI‑compatible gateway that exposes one API endpoint to route requests to 40+ model providers, issue revocable virtual keys, enforce budgets before spend, and record usage.
Browser-based agent workspace and sandboxed app platform that lets organizations run AI agents to perform tasks and build shareable 'Gadgets'. Uses Gatekeepers for fine-grained, zero-trust access control and runs on Cloudflare Workers with multi-LLM support.
Runs a local-first AI agent runtime that drives your desktop and automates workflows — browsing, file edits, approved shell commands, document extraction, and scheduled tasks — while integrating local or cloud LLMs (llama.cpp/TurboQuant) and embedding as an HTTP service or Tauri sidecar.
Indexes mixed-format folders locally into a zero-config, Elasticsearch-compatible search engine offering keyword, semantic, vector and hybrid retrieval. Embeds on ingest, provides per-agent namespaced memory and AST-aware code indexing in a single static binary with no external embedding key.
Provides a unified tool catalog and proxy for AI agents: one team token lets agents call thousands of third-party endpoints (and your team’s keys) with per-call pricing. Injects credentials server‑side so agents never hold provider secrets, and exposes CLI/skill recipes and OAuth tools for team-wide use.
Runs persistent, self-hosted AI teammates that retain conversation, memory, routines and a sandboxed browser/shell. Supports bring-your-own models, local or remote sandbox providers, voice, team computers and integrations for auditable, controllable agent workflows.