AI Agent2026
Lets AI agents use a user's logged-in Chromium browser to read pages, fill forms, capture screenshots, and debug web workflows in an isolated Agent Window so the user's normal browsing is not interrupted.
AI Model2026
Provides a GGUF-quantized local build of Ornith-1.0's 9B dense model for offline inference and terminal-focused coding agents. Supports OpenAI-compatible tool-calling, a 256K context window, and runs via llama.cpp or Ollama on a single high-memory GPU.
AI Infra2026
Streams routed experts from disk and treats storage, RAM and VRAM as a single inference hierarchy so MoE models (hundreds of billions to trillions of parameters) can run on consumer or heterogeneous hardware; single-file C engines with zero runtime deps and optional Vulkan/CUDA/Metal backends, speed governed by placement and disk I/O.
AI Model2026
Provides GGUF-quantized local-deploy weights for a 1B MiniCPM5-derived conversational LLM, embedding a 'thinking' chat template and supporting up to 128K-token context; ships Q4/Q5/Q8/F16 quant files (Q8_0 recommended) for llama.cpp, Ollama, and LM Studio.
AI Model2026
Provides pre-converted colibrì-format int4 weights so GLM-5.2 (744B MoE) can run by streaming routed experts from disk on a consumer machine with ~25 GB RAM. Includes MTP shard for lossless speculative decoding; requires the colibrì engine and ~400 GB NVMe.
Chatbot2026
Self-hosted, multi-user, multi-agent AI assistant with a web dashboard, CLI, IM channel integrations, cron automation, RAG knowledge bases, and ACP IDE delegation. Runs as a single-process local-first service with pluggable workspace backends and plugin extensibility.
AI API2026
Captures an app's network traffic, extracts its authentication/session bundle, and auto-generates an editable Python client to call the app's API. Supports mitmproxy, cURL and HAR capture backends and provides Session helpers for replay and token refresh.
AI Model2026
Provides low-bit quantized Hy3 (hy_v3) GGUF model weights and mixed-precision quantization recipes for running Hy3 on llama.cpp, with optional MTP self-speculative decoding and imatrix-based calibration for improved quality/speed trade-offs.
AI Dataset2026
Provides live Codex-CLI agent run traces from GPT-5.6 Sol capturing coding, debugging, security reviews, and harness/seed workflows in cumulative next-action prefixes — suitable for supervised fine-tuning and analysis of tool-using coding agents.
AI Infra2026
Provides a unified tool catalog and proxy for AI agents: one team token lets agents call thousands of third-party endpoints (and your team’s keys) with per-call pricing. Injects credentials server‑side so agents never hold provider secrets, and exposes CLI/skill recipes and OAuth tools for team-wide use.
AI Coding2026
Lets you write end-to-end tests that mix natural-language goals for an agent with deterministic locators and assertions across web and mobile; agent steps are recorded and replayed to avoid repeated model calls and fit CI workflows.
AI Coding2026
Acts as a proxy that incrementally compresses LLM conversation history for coding agents so a single session can run for months while using far fewer tokens. Compression is model-driven, reversible, and designed to preserve a stable KV-cache prefix so attention and billing remain efficient.