Introducing Internal Knowledge Search and Spaces

The enterprise is finally getting what the open web had from day one: a search engine that actually works. Perplexity's move into Internal Knowledge Search and Spaces isn't just a feature expansion—it's a declaration that the AI battleground has shifted from the public internet to the firewall's dark side. If you're not indexing your own data, you're already behind. This signals a maturation of the stack. We've spent two years chasing RAG and hallucination fixes; now the game is retrieval orchestration over privileged, internal corpora. Spaces, meanwhile, are cyber containers for collaboration—think a blend of vector database, wiki, and shared context. That's the seed of AI-native work, where the conversation *is* the artifact, not the document. It connects to compute too: internal search at scale is a heavy hammer on retrieval pipelines. This isn't trivial—latency and governance suddenly matter more than cool demos. For CISOs and CTOs, this is the moment AI companies become trusted infrastructure, not just clever interfaces. The internet was the first knowledge graph. Your enterprise is the second—and it's the one that actually pays.