Provides a long‑lived, in‑process file and content search library for editors and AI agents, with typo‑resistant fuzzy matching, frecency‑ranked results, background watchers, and a lightweight in‑memory content index — optimized for repeated searches in long‑running processes.
Provides ultra-fast, typo-tolerant file search and grep tuned for Neovim and AI agents, with built-in memory (frecency, git status, size, definition matches). It reduces agent token use and speeds developer file discovery in large repos.
Indexes any repo into a knowledge graph of dependencies, call chains, and execution flows, then feeds it to AI coding agents via MCP so they stop missing context. Ships as a CLI plus a zero-install browser graph explorer with chat.
Deploys autonomous AI agents that dynamically attack running apps and return validated proof-of-concept exploits instead of static-analysis noise. Specialized agents cover IDOR, injection, SSRF, XSS, and auth flaws, with HTTP proxy and CI/CD hooks.
Seven-week course that builds a production RAG system from scratch — an arXiv paper assistant that starts with BM25 keyword search, then layers hybrid vector retrieval, local-LLM generation, Langfuse monitoring, and an agentic LangGraph Telegram bot.
Wraps 20+ AI coding CLIs — Claude Code, Codex, Gemini CLI, Cursor Agent — in one cross-platform desktop app so agents run file, document, and data tasks without a terminal. Adds parallel multi-agent runs and cron-scheduled jobs for unattended work.
Deep research agent for complex, long-horizon research and prediction tasks. Pairs a 256K context window with up to 300 tool calls per query for web search, extraction, and code execution. Ships as open 30B and 235B models scoring 82.7% on GAIA.
Provides hierarchical, versioned semantic memory for AI agents with Git-like branching, commits, and rollbacks—using semantic paths and cryptographic provenance instead of opaque vector stores. Designed for branch-aware, auditable memory in multi-agent and production workflows.
Extensible AI coding-agent toolkit offering a terminal-first coding agent CLI, a unified multi-provider LLM API, TUI and web UI libraries, Slack integration, and vLLM pod support—built to prototype and run agent-driven developer workflows.
A TypeScript agent harness split into composable npm packages: a unified LLM API across OpenAI, Anthropic and Google, an agent runtime with tool calling and state, a self-extensible coding-agent CLI, and a differential-rendering terminal UI library.
Framework for building multi-modal AI agents that watch, listen, and reason over live video, pairing vision models (YOLO, Roboflow, Moondream) with LLMs like Gemini and OpenAI. Agents join calls in ~500ms and keep audio/video latency under 30ms.
Write repository automation as natural-language markdown that compiles into deterministic GitHub Actions workflows running AI agents. Agents run read-only by default and write only via sanitized safe-outputs. Works with Copilot, Claude, Codex, or Gemini.