Provides a deployable personal AI assistant that runs locally or in the cloud, supports multi-channel chat, extensible Skills/Plugins, and local-model runtimes. Key features include three-layer memory, kernel-level sandboxing and tool/file guards, and bundled QwenPaw-Flash local models for zero-API deployments.
Runs autonomous AI agents in isolated containers with declarative YAML policies that enforce filesystem, network, process, and inference controls. Provides credential providers, inference routing, hot-reloadable network/policy updates, and formal verification of policy changes for auditable agent execution.
Unmixes green‑screen pixels with a neural model to recover straight (unmultiplied) foreground color and a clean linear alpha for every pixel, preserving hair, motion blur and translucency. Produces VFX‑standard EXR outputs, supports optional AlphaHint generators (GVM/VideoMaMa) and Docker/consumer‑GPU optimizations.
Visualizes live global data on a CesiumJS 3D globe via a plugin-driven pipeline and real-time WebSocket DataBus. Supports dynamic plugin marketplace, an opt-in Agent Bus for external LLM/MCP control, and self-hosting with Docker and PostgreSQL.
Deploy and manage applications and containers to your own servers or Openship Cloud from a single desktop, web, or CLI interface. Built-in CI/CD with push-to-deploy and preview environments, automatic SSL, managed databases, CDN, backups, and multi-node portability for VPS-to-production workflows.
Aggregates 60+ real-time OSINT feeds into a self-hosted geospatial dashboard and exposes an HMAC-signed agentic AI command channel so LLM-driven agents can query and act on live telemetry; privacy is experimental.
Self-hosted personal finance manager that keeps all account data on your server — supports multi-currency accounts, bank sync, rules-based auto-categorization, budgets and asset tracking. Distinguishes itself by privacy-first design and optional self-hosted LLM agents for local data queries; suitable for users comfortable running a server.
Turns a single research idea into runnable experiments and a conference-ready paper by orchestrating an LLM-driven end-to-end workflow (literature → design → code → sandboxed runs → analysis → writing). Provides human-in-the-loop checkpoints, domain-specialist executors, and multi-layer citation verification.
Orchestrates LLM-powered coding agents in isolated sandboxes to automate code edits and review pipelines. Provider-agnostic (Docker, Podman, Vercel), supports branch strategies, session capture, reusable sandboxes and structured outputs.
Centralizes trip planning on a self-hosted server: collaborative itinerary editor with interactive maps, expenses, packing lists, reservations and PWA/offline support. Includes a built-in MCP (Model Context Protocol) server so AI assistants can read and automate trips via OAuth 2.1.
Provides a persistent, typed semantic memory layer for AI agents—supports remember, recall, and answer primitives so agents retain long-term context. Writes are instantly searchable and retrieval uses an information-theoretic engine, avoiding separate vector DBs or indexing delays.
Self-hosted web and mobile interface for running and managing a Hermes autonomous agent — chat, persistent sessions, workspace file browsing, task scheduling, and tools with near-1:1 parity to the CLI. Designed for self-hosted homelab or VPS deployments; depends on a running Hermes Agent.