Governance-First AI Execution Platform
Prioritised Governance for AI Execution
Run governed, multi-node AI workloads with policy controls, auditability, and sovereignty built in from the start.
SUMO-TX is a governance-first, CPU-distributed AI execution platform designed for organisations that require predictable, auditable, and cost-controlled AI workloads.
Rather than focusing on GPU-centric model training, SUMO-TX provides a deterministic governance and execution layer that orchestrates AI tasks across distributed node environments, ensuring policy enforcement, traceability, and reliability at scale. Built natively for Microsoft Azure, SUMO-TX enables organisations to run AI workloads within their own subscription while prioritising request tracing, version visibility, rate controls, and structured audit evidence — without reliance on opaque external systems.
Designed for real-world AI governance and execution — not demo environments.
Prioritised Governance
Policy enforcement, request tracing, version visibility, and rate controls are designed into every governed workflow.
Deterministic Orchestration
Task graphs progress with backpressure control, retries, and explicit workflow gating for predictable operations.
Message-Driven Architecture
All components communicate via distributed message passing, ensuring decoupling, scalability, and system resilience.
Distributed Execution
Run AI workloads across multiple CPU nodes (up to 32+ per layer) with explicit orchestration and failure isolation.
API-First Control Layer
Full system control via versioned APIs, enabling integration with enterprise systems, monitoring, and automation pipelines.
Audit & Evidence
Every decision and execution path is recorded and traceable, enabling audit, compliance, replay, and evidence-backed governance.
Sovereign Deployment
Runs entirely within the customer's Azure environment — no external dependency or data leakage.
Developed by OrkinosAI Labs | Runs natively on Microsoft Azure