# Enterprise AI eventually becomes a platform. > Teams start with separate tools and models. Then the company inherits repeated integrations, different access rules, multiple bills and no shared operating view. ## Move from disconnected solutions to shared infrastructure. **Fragmented AI stack** - Every product connects to company systems separately - Access rules are rebuilt in each tool - Subscriptions and APIs are paid in different places - Agents and apps cannot reuse shared components - Support gets harder with every new tool **One Wide Moat platform** - Connect systems once through shared connectors - One identity and access layer - One catalogue of approved models - Central budgets and token-spend control - Shared skills, data and policies for every agent and app ## Connect once. Govern centrally. Reuse across every AI use case. Wide Moat does not force useful tools out. It gives them one enterprise foundation. ## One foundation replaces many separate control planes. - **Connections** — Shared connectors for assistants, agents and applications. - **Access** — One identity and permission model across AI use cases. - **Models** — Route work across approved internal and external models. - **Spend** — Central budgets, limits and visibility into token costs. - **Building blocks** — Shared skills, data and policies across the platform. - **Operations** — One managed platform instead of a fragile tool stack. ## Your systems of record and useful specialist tools. ERP, CRM, BI, repositories, workflow automation and approved AI tools remain in place. Wide Moat gives them shared infrastructure. ## When different use cases begin to share the same foundation. Several functions, sensitive data, repeated integrations, multiple models and the need to manage spend centrally are signs that point tools are no longer enough. ## Identify what your next AI use cases should share.