Bridges MCP-capable AI agents (Claude, Copilot, Cursor) to 150+ offensive-security tools, letting them autonomously run pentests, vulnerability scans, and bug-bounty workflows. A decision engine picks the right tools and adapts as findings emerge.
A ~5,000-line Python LLM inference engine that re-implements SGLang's serving optimizations — radix KV-cache reuse, chunked prefill, overlap scheduling, tensor parallelism — as a fully type-annotated reference instead of a black box.
Build and self-host production voice agents with a drag-and-drop workflow builder, real-time telephony integration, and pluggable LLM/STT/TTS backends. Docker-first with an optional managed cloud offering for teams that want faster onboarding.
Eight example apps for building with the Claude Agent SDK: an IMAP email assistant, a multi-agent research system, an Excel agent, a React/WebSocket chat UI, a .docx resume generator, and hello-world session demos. Local-only, not production.
Turns papers, repositories, or natural-language research goals into local-first executable 'quests' that automate reproducible experiments, branching, and result-to-paper workflows. Preserves experiment history, supports web/TUI/connectors, and keeps human takeover and inspection simple.
Provides Gymnasium-style APIs and tooling to run isolated, networked execution environments for agentic reinforcement learning. Offers async/sync EnvClients, Docker/Kubernetes container providers, a web UI and CLI for scaffolding and deploying environments (Hugging Face Spaces); experimental and evolving.
Runs text-to-speech with instant voice cloning fully on-device, from phones to GPUs. Built on small LLM backbones (120M-360M params) plus a 50Hz neural codec; clones a voice from ~3 seconds of audio across English, Spanish, German, and French.
Turns clinical text into structured, de-identified clinical signals—entity extraction and PII de-identification—that run entirely on local hardware. Provides 1,000+ specialized medical NER models, multilingual support, Apple MLX acceleration, and Apache‑2.0 licensing.
Autonomously performs end-to-end data science tasks — from cleaning and exploration to modeling, visualization, and analyst-grade reports — via an agentic LLM. Open-source model, code, datasets and demos; supports vLLM deployment, Jupyter/CLI/Web UIs, and OpenAI-style APIs.
Terminal-based coding agent that reads and edits code, runs shell commands, and fetches web pages while planning multi-step tasks autonomously. A Ctrl-X toggle drops into a raw shell, and ACP support plugs it into Zed and JetBrains IDEs.
Orchestrates multiple AI providers to generate context-aware attack payloads, scan web targets for 45+ vulnerability types, and produce compliance-mapped reports. Supports dynamic provider failover, RAG-indexed CVE intelligence, browser automation, and AI triage; requires API keys and authorized testing.
Generates production-grade synthetic datasets from scratch or from seed data using dependency-aware samplers, LLM-backed text columns, built-in validators, previewing, and LLM-as-judge scoring.