Turinton OS is an AI infrastructure platform that deploys complete AI ecosystems on local, edge, or on-premise hardware, eliminating the need to build AI stacks from scratch. It connects to existing ERP, CRM, and data warehouses without data migration, using a context graph to orchestrate business data into a unified knowledge layer. The platform ships with templatized applications for manufacturing, banking, and enterprise operations, with customers typically recovering their three-year total cost of ownership in under six months.
Funding
Funding not disclosed
Founders
Product
Problem
Enterprises often find that cloud-based AI infrastructure fails to meet operational, data-sovereignty, latency, or compliance requirements. Building and integrating local AI infrastructure—spanning GPUs, models, data pipelines, and application frameworks—is complex, time-consuming, and costly, delaying production AI deployments by months or years.
Solution
Turinton OS provides a complete AI operating layer that sits between a company's hardware and its AI applications, handling the integration work automatically. It connects to existing ERP, CRM, and data warehouse systems without requiring data migration, and builds a unified context graph that maps business data for reuse across all applications. The platform supports deployment on local infrastructure, including air-gapped environments, and offers templatized, industry-specific applications that can be customized without rework. Turinton OS is AI-native, exposing every capability as an API, and interoperates with MCP-compatible agents, enabling rapid deployment of production AI in 8–12 weeks versus the typical 6–18 months.
Target Audience
Primary customers are mid-size to large corporations in manufacturing, banking, financial services, healthcare, and enterprise operations that need to run AI on local or distributed infrastructure for reasons of data sovereignty, latency, compliance, or operational control.
Features
- Zero-ETL connectivity that integrates with existing enterprise systems without data migration
- Context Graph technology that creates a living, reusable map of business data across the organization
- On-premise and air-gapped deployment options for data that cannot leave the building
- AI-native architecture where every capability is exposed as an API from day one
- Native MCP (Model Context Protocol) interoperability with external AI agents
- Templatized applications across manufacturing (12+ templates), banking (26+ templates), and enterprise operations (40+ templates)
- Hardware-agnostic design that works with recommended GPU/DGX systems or existing local infrastructure
- Scalable deployment options from single production lines to enterprise-wide, high-concurrency configurations