Enterprise AI
Compare enterprise AI search tools for company knowledge: Glean, Microsoft 365 Copilot Search, Gemini Enterprise, and Perplexity Enterprise across connectors, permissions, grounding, agents, governance, and rollout risk.
Comparison
| Option | Best for | Strengths | Tradeoffs | Use when |
|---|---|---|---|---|
| Glean | Cross-app workplace search and knowledge discovery across many enterprise systems | Strong positioning around enterprise data, relevance, connectors, personalization, and work AI. | Requires connector coverage, identity integration, and change management across many systems. | Your core pain is that knowledge lives across too many workplace apps. |
| Microsoft 365 Copilot Search | Microsoft 365 organizations that want AI-powered universal search inside the Microsoft work graph | Fits Microsoft 365 identity, files, Teams, Outlook, SharePoint, connectors, and admin controls. | Less complete if important knowledge lives outside Microsoft and is not connected well. | Most company knowledge and user workflows already live in Microsoft 365. |
| Gemini Enterprise | Google Cloud and Workspace teams combining intranet search, assistants, agents, and connectors | Positioned as an intranet search, AI assistant, and agentic platform with third-party connectors. | Best fit depends on Google Cloud strategy, data-source support, and governance readiness. | You want enterprise search tied to Google Cloud AI and agent workflows. |
| Perplexity Enterprise | Research-heavy teams that want secure answers across files, tools, and web research | Useful for knowledge work that mixes internal files, external research, and model choice. | May not replace a full enterprise search deployment when connector governance is the main project. | The team needs deep research and answer synthesis more than classic intranet search. |
Enterprise search fails when employees see results they should not see or cannot find content they are allowed to use. The AI answer layer must respect the same identity, sharing, and tenant boundaries as source systems.
A demo usually shows a clean knowledge base. Real deployments depend on connector quality, sync frequency, metadata, deletion handling, and search relevance across messy systems.
The value is not only search speed. Track whether users get accurate, cited, complete, and actionable answers without asking another person.
Decision Rules
Choose Glean when cross-application enterprise search is the main problem.
Choose Microsoft 365 Copilot Search when Microsoft 365 is the center of work and identity.
Choose Gemini Enterprise when Google Cloud, connectors, and agent workflows are strategic.
Choose Perplexity Enterprise when research synthesis across files and web sources matters most.
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OpenFAQ
Enterprise AI search combines search, retrieval, and generative answers across company data sources while respecting identity, permissions, and governance controls.
Not exactly. RAG is a retrieval-and-generation pattern. Enterprise AI search is a product category that also includes connectors, identity, permissions, relevance, governance, and user experience.
Test connector coverage, permission enforcement, source citations, stale content handling, answer quality, admin controls, logging, and adoption in real workflows.
Source Links
Reference
Glean product page for searching across workplace tools.
OpenReference
Microsoft Learn documentation for Copilot Search.
OpenReference
Google Cloud documentation for Gemini Enterprise as intranet search, assistant, and agentic platform.
OpenReference
Perplexity product page for enterprise research across files and tools.
OpenThe strongest decision is always local to your workflow. Save the vendor links, define a representative task, record the exact prompt or command, and compare the final evidence instead of the marketing claim.
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