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Zyrabit Platform

Zyrabit Platform is an enterprise-grade AI infrastructure layer designed for on-premise and private cloud environments. It provides a modular, containerized architecture to deploy, manage, and scale local AI capabilities while maintaining strict data sovereignty and verifiable evidence boundaries.

đŸŽĨ See it in Action: True Sovereign AI​

Curious about what this looks like in practice? We've recorded a hands-on demo showcasing Zyrabit Platform running 100% offline.

Watch the system process voice commands and capture images in real-time without relying on a single external API or internet connection. This is what true local intelligence looks like.

👉 Watch the Offline Demo Here

ℹī¸ Note: The video audio is in Spanish.

🤖 Sovereign Runtime for AI Agents​

Zyrabit SLM serves as a local-first backend and security firewall for autonomous AI agents (Cursor, Antigravity, AutoGen, CrewAI, LangGraph, and Cline):

  • Zero-Trust Tool Execution (MCP): Safely exposes local file operations, databases, and internal APIs to agents via the standard Model Context Protocol.
  • PII & Secret Protection: Outbound agent prompts are automatically scrubbed of credentials, API keys, and sensitive personally identifiable information before hitting models.
  • Sovereign Agent Memory: State, conversation history, and document embeddings stay local in SQLite WAL and ChromaDB — zero external data egress.

Architecture & Design Principles​

Zyrabit is built on a zero-trust architecture, ensuring that data processing remains entirely within the host network perimeter. It integrates vector databases, local inference engines, and workflow automation into a unified, reproducible deployment model.

Core Capabilities​

  • Private RAG & Agent Memory: A high-performance vector retrieval system coupled with local language models for deterministic, context-aware querying of proprietary datasets.
  • Autonomous Agent Tooling (MCP): Pre-packaged Model Context Protocol servers allowing AI agents to interact with on-premise infrastructure safely.
  • Hardware-Aware Inference: Dynamic compute routing that automatically maps execution to the optimal available backend (Apple Metal, NVIDIA CUDA, or CPU/AVX2) without manual configuration overhead.
  • Native Observability: Integrated telemetry stack utilizing Prometheus and Grafana to expose critical metrics, including inference latency, VRAM allocation, and query throughput.
  • Workflow Orchestration: Native integration with n8n to enable the design and execution of complex, API-driven AI pipelines.

Target Environments​

Zyrabit is engineered for deployments that require stringent data governance and low-latency local execution:

  • Sovereign AI Agents operating on corporate codebases and confidential data.
  • Air-gapped enterprise networks.
  • Compliance-regulated industries (Healthcare, Finance, Public Sector).
  • Edge computing nodes and localized data centers.

Next Steps​

To begin deploying the Zyrabit stack, proceed to the Quickstart Fundamentals guide.