Parses PDF resumes into structured JSON using LLMs, enriches profiles with GitHub signals, and outputs explainable category scores, evidence, bonuses and deductions. Runs fully local with Ollama or via Google Gemini; designed for reproducible, fairness-constrained resume scoring in hiring workflows.
Compiles an agent's raw chat logs, documents, and tool traces into three persistent layers — index, learned skills, and user memory — so context survives sessions. Claims 92% Locomo-benchmark accuracy and up to 95% lower token cost than replaying history.
Collaborates on web tasks in real time: edit its plan before it runs, pause and grab the browser mid-task, and approve irreversible clicks before they happen. A research prototype for studying human-in-the-loop oversight instead of full autonomy.
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.
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.
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.
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.