Provides a conditional memory module that performs O(1) N‑gram lookups and fuses static embeddings into transformer hidden states — enables offloading large embedding tables to host memory with minimal inference overhead.
AI Agent2026
Models an AI agent's context as a file system, unifying memory, resources, and skills instead of flat vector RAG. Uses L0/L1/L2 tiered loading to cut tokens, directory-recursive plus semantic retrieval, and visualized retrieval traces for debugging.
AI Agent2026
Provides cross-platform semantic memory for AI coding agents by turning human-editable Markdown logs into a rebuildable Milvus “shadow” index and syncing memories across plugins (Claude Code, OpenClaw, OpenCode, Codex). Supports progressive retrieval, hybrid dense+BM25+RRF search, smart deduplication, live sync, and local ONNX embeddings.
AI Deploy2026
Runs a local-first, full AI stack—LLM inference, chat UI, voice, agents, workflows, RAG, and image generation—deployable with one command. Auto-detects hardware and bootstraps a small model for instant chat while larger models download; supports Linux, Windows, macOS and optional cloud/hybrid modes.
AI Deploy2026
Local LLM inference server for Apple Silicon that exposes an OpenAI-compatible API and a macOS menubar app. Uses continuous batching and a two-tier KV cache (RAM + SSD in safetensors) to persist context across restarts, enabling practical multi-model serving and fast local coding workflows.
AI Infra2026
Acts as an OpenAI‑compatible local and cloud gateway that routes requests across 100+ LLM providers with smart routing, load balancing, retries and fallbacks. Adds policies, rate limits, semantic caching and observability for reliable, cost‑aware inference in Docker, Electron or npm installs.
MCP Server2026
Indexes codebases into a persistent, queryable knowledge graph for AI coding agents, enabling full-repo indexing in minutes and sub-millisecond structural queries. Bundles 158 vendored tree-sitter grammars, a Hybrid LSP resolver, built-in embeddings, and 14 MCP tools for search, trace, and architecture analysis.
MCP Server2026
Provides persistent, searchable memory for coding agents (Claude Code, Cursor, Gemini CLI, etc.), automatically capturing tool usage and session facts. Combines BM25, vector embeddings and a knowledge graph for hybrid retrieval, reducing token costs and re-explaining between sessions.
AI Coding2026
Builds a local structural knowledge graph of a codebase so AI coding assistants read only the minimal, relevant code during reviews and daily tasks—reducing tokens used while providing blast-radius impact analysis, incremental updates, and MCP integrations.
AI Client2026
Local-first desktop workbench that scrapes job leads, filters low-quality postings, scores candidate fit with explainable rules and vector matching, and generates tailored resumes, cover letters, and outreach drafts while keeping data on-device.
AI Agent2026
Provides AI coding agents with persistent memory inside an Obsidian vault—preserving session context, decisions, and notes across sessions. Integrates hooks/commands for Claude Code, Codex CLI, and Gemini CLI and optionally uses QMD for semantic recall; aimed at developer workflows.
AI Infra2026
Provides a single persistent database and open protocol so multiple AI tools share the same memory — built-in vector search, an AI gateway, and capture/skill extensions. Best for teams and power users who want a unified, self-hosted agent memory instead of siloed notes or per-tool caches.