Manages polyglot monorepos by caching unchanged outputs and running only affected tasks. Built with Rust and extensible in TypeScript; includes integrated CI features (remote caching, task distribution) and AI-native tooling such as a CLI optimized for autonomous agents and self-healing CI.
Rust-native, event-driven trading platform for backtesting and live execution across crypto, forex, equities, and futures on 27+ venues. The same strategy code runs in nanosecond backtests and in production, giving true research-to-live parity.
Terminal rebuilt around AI agents: orchestrate Claude Code, Codex, and Warp's own agent in parallel, each with codebase indexing and scoped permissions. Run them locally or in the cloud, and bring your own model via Bedrock, LiteLLM, OpenRouter.
Rust-and-Python toolkit that serves open-source LLMs (Llama, Falcon, Mixtral, StarCoder) over HTTP/gRPC with tensor parallelism, continuous batching, Flash/Paged Attention and quantization. Now in maintenance mode, pointing users toward vLLM and SGLang.
Centralizes logs, metrics, traces, frontend RUM and LLM observability into one self-hostable platform, using Parquet + S3-native storage and SQL/PromQL querying to reduce long‑term storage costs and unify telemetry analysis.
Self-hosted AI coding assistant you run on your own hardware as an alternative to cloud Copilot. Offers context-aware completion, an in-IDE answer engine and chat, using RAG over your repositories so suggestions match your team's code.
Detects file content types with a compact deep‑learning model that runs in milliseconds on a single CPU. Trained on ~100M samples across 200+ content types; offered as a Rust CLI plus Python, JS, and Go bindings for large‑scale security and file‑routing use.
GPU-accelerated code editor written in Rust, organized like a game engine to render its UI via shaders. Includes native agentic coding over the open Agent Client Protocol, multiplayer editing, LSP/DAP, and an open edit-prediction model.
Produces real-time 3D reconstructions from multi-view images using Gaussian splatting, with on-device training and interactive viewing across native desktops, Android, and the browser. Uses WebGPU and the Burn ML framework to ship dependency-free binaries, a CLI, live training visualization, and streaming .ply support.
Continuously captures your screen and spoken conversations, transcribes them in real time, generates summaries and action items, and exposes a memory-backed chat that can retrieve what you've seen and heard. Works across desktop, mobile and wearable devices and supports local SDKs and cloud sync.
Connects multiple Macs and Linux machines into one cluster to run models too large for any single machine. Auto-discovers peers, shards a model across them via tensor parallelism, and exposes OpenAI-, Claude-, and Ollama-compatible APIs.