AI API2026
Provides short-lived, copy-pasteable API tokens that let developers access 90+ LLMs (GPT‑5.5, Claude, Gemini, Grok, etc.) without a credit card or registration. Keys are refreshed multiple times daily, each carries a $20–$100 budget and expires in 24–48 hours. Works with any OpenAI-compatible client via a single base URL.
AI Infra2026
Compresses high-dimensional embeddings into low-bit TurboQuant indexes for fast, memory-efficient local vector search. Supports online ingest (no train/rebuild), SIMD kernels that match or beat FAISS, per-vector length-renormalization, and runtime allowlists — suited for privacy-sensitive, low-latency RAG.
AI Agent2026
Provides a cloud-backed shared memory and skill-propagation layer for coding agents: captures session traces, mines recurring patterns into reusable SKILL.md, and shares capabilities across agents in real time. Features hybrid semantic+lexical search, BYOC storage, and a VFS for traces — built for team workflows and agent orchestration.
AI Agent2026
Provides a brain layer for AI agents that synthesizes answers, traverses a self-wiring knowledge graph, and highlights gaps in team knowledge. Ships hybrid retrieval, citation-aware synthesis, and MCP integrations for Claude/Codex to power meeting prep and company-wide memory.
MCP Client2026
Stores conversation history verbatim and retrieves it via local semantic search with a structured index (wings/rooms/drawers). Pluggable vector backends and a local-first default mean high recall (benchmarked) without cloud or API keys—useful for agent memory and private RAG.
AI Agent2026
Provides fully local long-term and symbolic short-term memory for AI agents via a 4-tier layered pipeline and Mermaid canvases, with zero external API dependencies. Key features: lossless drill-down from personas to raw traces, hybrid retrieval, and ready integrations for OpenClaw and Hermes.
AI Client2026
Turns your documents into a persistent, interlinked personal wiki by incrementally reading sources, generating wiki pages, and keeping knowledge up to date. Features two-step chain-of-thought ingest, graph-based relevance with Louvain clustering, optional embedding search (LanceDB), and a local HTTP API for agent integration.
AI Dataset2026
Curated 100K subset of geometrically diverse CAD construction sequences sampled from a 1M agentically synthesized corpus — each item includes executable CadQuery scripts, 8 rendered views, STL/STEP exports, and precomputed DINOv3 embeddings for retrieval and benchmarking.
AI Dataset2026
Provides one million executable, human-readable CadQuery construction sequences synthesized by an LLM-in-the-loop—each sample includes renders, STL/STEP exports, precomputed DINOv3 embeddings and a FAISS index. Designed for training and benchmarking text/image→3D and CAD-program generation models (Apache-2.0).
AI Model2026
Produces 384‑dim multilingual (and code) embeddings with up to 32,768 token context, optimized for low‑latency production retrieval. Compact 97M model with ONNX/OpenVINO and vLLM/GGUF deployment options for edge and high‑throughput use.
AI API2026
Provides a single OpenAI-compatible /v1 API that aggregates the free tiers of 16 LLM providers into one unified endpoint. Features smart routing and automatic failover, per-key free-tier tracking, encrypted key storage, embeddings/media routing, and a Docker one-liner for local use.