SWIRL for OEMs and MSPs: The Enterprise Knowledge Layer You Don't Have to Build

Every business is trying to make AI work with its own data. But that data is scattered across Microsoft 365, Salesforce, file shares, databases, and 150+ other systems, and the usual answer is a pipeline: copy it, index it, sync it, and secure it all over again. SWIRL takes the opposite position: bring access together, not the data. It is a live query federation layer; one governed API and experience for employees, AI agents, and your product. At query time it pushes user-aware queries to each source, then normalizes, deduplicates, and relevance-ranks the results. Data never moves; permissions are enforced at the source on every query. 0:00 The problem: AI needs your data, and it's scattered 0:11 Why copy-and-index approaches fail 0:21 SWIRL: one governed knowledge layer for people, agents, and applications 0:44 Embed it: your product, your brand, any LLM The demo's proof point, at 0:37: SWIRL finds every version of a policy across systems, identifies the trusted one, and grounds the AI answer in it, with citations. That is one example of the intelligence applied to every result set. For OEMs, MSPs, enterprise software, industry solutions, AI platforms, and systems integrators: embed SWIRL behind your UI via REST and MCP, or ship a white-label experience, with any LLM, in your environment or your customer's. Talk to an engineer: https://swirlaiconnect.com/swirl-for-embedding Docs: https://docs.swirlaiconnect.com Try the SWIRL skill in Claude Cowork: claude plugin marketplace add swirlai/swirl-claude-plugin #EnterpriseSearch #OEM #MSP #RAG #FederatedSearch #MCP #AI #KnowledgeManagement