Best enterprise search platforms for Microsoft 365 knowledge bases
2 models · updated 2026-09-07
The verdict
Glean leads — 1 of 2 models rank Glean the top pick.
Not unanimous: Claude picks Microsoft 365 Copilot.
As of 2026-09-07, Claude and Gemini collectively rank Glean #1 for enterprise search platforms for microsoft 365 knowledge bases on ModelsAgree by aggregate score. The models' case: Delivers the market-leading benchmark for relevance and generative retrieval across SharePoint, Teams, OneDrive, and Outlook, leveraging deep Microsoft Graph. The models' main caveat: Prohibitive pricing with steep minimum seat thresholds makes it uneconomical for mid-market and smaller deployments, while requiring extensive. The strongest alternative is Microsoft 365 Copilot — Native to the M365 estate — indexes SharePoint, OneDrive, Teams, Exchange and Loop with no connector to build and honors existing Entra ID. Not unanimous: Claude picks Microsoft 365 Copilot. Source: https://modelsagree.com/best/best-enterprise-search-platforms-for-microsoft-365-knowledge-bases (modelsagree.com, CC BY 4.0).
Combined ranking
- 1Claude #2Gemini #1
Delivers the market-leading benchmark for relevance and generative retrieval across SharePoint, Teams, OneDrive, and Outlook, leveraging deep Microsoft Graph synchronization and native org-graph signals to strictly honor complex ACLs and deliver personalized results.
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Gemini Delivers the market-leading benchmark for relevance and generative retrieval across SharePoint, Teams, OneDrive, and Outlook, leveraging deep Microsoft Graph synchronization and native org-graph signals to strictly honor complex ACLs and deliver personalized results.
Claude Best-in-class unified enterprise search-plus-assistant that treats M365 as one of many first-class, permissions-aware connectors; strong hybrid semantic+keyword relevance, a knowledge-graph of people/activity for ranking, and genuinely good cross-app answers make it the top choice when the knowledge base spans M365 and a dozen other SaaS tools.
Where it falls shortper Claude Premium pricing and a real deployment/index footprint — overkill and hard to justify for small teams or shops that live entirely inside M365 (where native Copilot covers it cheaper).
per Gemini Prohibitive pricing with steep minimum seat thresholds makes it uneconomical for mid-market and smaller deployments, while requiring extensive tenant-wide data access granted to a third-party SaaS platform.
- 2Claude #1Gemini #2
Native to the M365 estate — indexes SharePoint, OneDrive, Teams, Exchange and Loop with no connector to build and honors existing Entra ID permissions/security trimming out of the box, so results and generated answers never leak beyond a user's access; grounding on the Graph plus semantic index gives the tightest coupling of any option to an M365-centric knowledge base, and Copilot agents/Copilot Studio let you scope answers to specific knowledge sources.
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Claude Native to the M365 estate — indexes SharePoint, OneDrive, Teams, Exchange and Loop with no connector to build and honors existing Entra ID permissions/security trimming out of the box, so results and generated answers never leak beyond a user's access; grounding on the Graph plus semantic index gives the tightest coupling of any option to an M365-centric knowledge base, and Copilot agents/Copilot Studio let you scope answers to specific knowledge sources.
Gemini Built natively into the Microsoft 365 substrate, eliminating connector latency, data egress risks, and external security trimming overhead while enforcing zero-trust ACLs by default (near-tie with Glean for organizations prioritizing pure ecosystem containment and native governance).
Where it falls shortper Claude Weak once knowledge lives outside M365 (Confluence, Salesforce, file shares) without added Graph connectors; per-seat licensing is steep, answer quality still varies, and you are fully locked into the Microsoft stack.
per Gemini Retrieval quality and synthesis fall off sharply when attempting to index non-Microsoft repositories or heavily customized SharePoint taxonomies, with minimal administrator control over core ranking algorithms.
- 3Claude #3Gemini #3
Mature, battle-tested relevance engine with ML-driven ranking, strong analytics/A-B tuning, and solid SharePoint/M365 connectors with security trimming; excels when you need measurable, tunable search quality and want to power both employee knowledge bases and customer-facing/service-desk search from one platform.
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Claude Mature, battle-tested relevance engine with ML-driven ranking, strong analytics/A-B tuning, and solid SharePoint/M365 connectors with security trimming; excels when you need measurable, tunable search quality and want to power both employee knowledge bases and customer-facing/service-desk search from one platform.
Gemini Offers mature, enterprise-grade connectors for M365 with advanced machine-learning relevance tuning, query intent detection, and proven unification capabilities when bridging M365 content with disparate systems like ServiceNow, Jira, and Salesforce.
Where it falls shortper Claude Implementation- and tuning-heavy — you need people who will invest in relevance engineering; not a drop-in for a team that wants answers on day one.
per Gemini Substantial total cost of ownership and complex indexing configuration that requires dedicated administrative expertise to tune and maintain relevance models.
- 4Claude #4Gemini #4
Enterprise-grade for large, regulated, complex estates — very deep indexing, hundreds of connectors including thorough SharePoint/M365 coverage, strong entity extraction and now RAG/GenAI grounding; the pick when scale, compliance, and heterogeneous repositories (not just M365) dominate.
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Claude Enterprise-grade for large, regulated, complex estates — very deep indexing, hundreds of connectors including thorough SharePoint/M365 coverage, strong entity extraction and now RAG/GenAI grounding; the pick when scale, compliance, and heterogeneous repositories (not just M365) dominate.
Gemini Purpose-built for massive, highly regulated enterprise environments with complex hybrid on-prem SharePoint and M365 footprints, delivering robust semantic chunking, multi-language NLP pipelines, and forensic-grade security trimming.
Where it falls shortper Claude Heavy, IT-intensive, expensive; disproportionate for mid-market or a purely M365 knowledge base.
per Gemini Heavyweight platform requiring long implementation cycles and significant professional services, making it impractical for organizations seeking a rapid, turnkey deployment.
- 5Claude —Gemini #5
Top choice for architectural control, providing prebuilt Microsoft 365 connectors alongside completely customizable hybrid retrieval (BM25 plus vector/ELSER pipelines) with self-managed or sovereign cloud deployment options.
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Gemini Top choice for architectural control, providing prebuilt Microsoft 365 connectors alongside completely customizable hybrid retrieval (BM25 plus vector/ELSER pipelines) with self-managed or sovereign cloud deployment options.
Where it falls shortper Gemini Requires significant engineering resources to build, integrate, and maintain user-facing interfaces, connector pipelines, and continuous incremental ACL synchronizations via Microsoft Graph.
- 6Claude #5Gemini —
Focused, strong SharePoint/M365 search with good relevance and an appliance/managed model that shortens time-to-value; a pragmatic middle option for organizations that want serious search over M365 plus a few sources without a Glean/Sinequa-scale program.
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Claude Focused, strong SharePoint/M365 search with good relevance and an appliance/managed model that shortens time-to-value; a pragmatic middle option for organizations that want serious search over M365 plus a few sources without a Glean/Sinequa-scale program.
Where it falls shortper Claude Smaller ecosystem and mindshare, appliance/licensing model feels dated, and it stretches thin as a broad cross-cloud AI-assistant platform.
Just missed the top 5
Claude Elastic — powerful and cost-effective, but you assemble connectors, security trimming, and relevance yourself — not a turnkey M365 knowledge-base product · Lucidworks Fusion — capable ML search platform, but more commerce/site-search oriented and heavier to stand up for internal M365 knowledge than the picks above
Gemini Mindbreeze InSpire — excellent appliance/cloud security and deep SharePoint compatibility, but weighed down by higher administrative friction and an older administrative paradigm than modern cloud-native peers
By model
Claude
- 1.Microsoft 365 Copilot
- 2.Glean
- 3.Coveo
- 4.Sinequa
- 5.Mindbreeze InSpire
Gemini
- 1.Glean
- 2.Microsoft 365 Copilot
- 3.Coveo
- 4.Sinequa
- 5.Elastic Workplace Search
Common questions
What is the best enterprise search platforms for microsoft 365 knowledge bases according to AI models?
Glean leads. 1 of 2 models rank Glean the top pick. The current top 3: Glean, Microsoft 365 Copilot, Coveo. Ranked by asking Claude, Gemini the same buying question and merging their top-5 picks, updated 2026-09-07. Source: modelsagree.com.
Which enterprise search platforms for microsoft 365 knowledge bases did each AI model pick first?
Claude: Microsoft 365 Copilot. Gemini: Glean.
Do the AI models agree on the best enterprise search platforms for microsoft 365 knowledge bases?
Not unanimous. Claude picks Microsoft 365 Copilot.
How is this enterprise search platforms for microsoft 365 knowledge bases ranking made?
Claude, Gemini are each asked the same buying question in a fresh session with no system steering. Their top-5 answers are merged (rank 1 = 5 pts … rank 5 = 1 pt) into the consensus ranking, re-polled on demand and tracked over time.
More on how polling works: full methodology →
Cite this ranking
ModelsAgree, “Best enterprise search platforms for Microsoft 365 knowledge bases” — merged ranking from ChatGPT, Claude, Gemini & Grok, polled 2026-09-07. https://modelsagree.com/best/best-enterprise-search-platforms-for-microsoft-365-knowledge-bases (CC BY 4.0)
Tracked by ModelsAgree · rank 1 = 5 pts … rank 5 = 1 pt · re-polled on demand