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What an enterprise knowledge platform must do
An AI agent is only as useful as the information it can retrieve and the authority it has to act. A knowledge platform should connect organizational sources to agent experiences, retrieve relevant material for a question, and expose enough source context for a user to verify the answer. It also needs to preserve access boundaries and let administrators govern both the sources and the agents that use them.
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For example, an employee might ask, “How do I file an expense report?” The agent should find current policy and process information the employee is allowed to see, identify where that information came from, and avoid inventing a procedure when the sources do not answer the question. If it can submit or change an expense report, that action needs controls beyond those used for read-only search.
Assess the platform as an operating system for knowledge-backed agents, not just as a search box or connector bundle. The required systems, content and policies in your environment determine whether a product’s documented features are useful in practice.
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Build a source and workflow inventory before vendor demos
List the repositories the agents need to use and the tasks they should support. Include the content and identity details that a connector count cannot tell you.
- Repositories: name each system, including document stores, collaboration tools, knowledge bases and workflow applications.
- Content: identify formats, content types, locations, metadata and sensitivity labels the agent must retrieve or filter on.
- Access model: record how the source represents user and group access, inherited permissions, guests, restricted areas and revoked access.
- Change behavior: ask whether edits, moves and deletions are reflected, how quickly they are reflected, and what happens during a connector outage.
- Workflows: distinguish questions answered by reading from operations that create, update, approve or send information.
For every required source, confirm that the connector supports the specific content, metadata, permission model and update behavior your use case depends on. Ask about live retrieval or write-back only where those capabilities are needed. A nominal connection to an app is not proof that its important content or controls are covered.
Compare architectures on operational fit
Two documented approaches illustrate the design choices. Microsoft describes Copilot connectors for unified search and agent knowledge, and its Retrieval API retrieves in place from SharePoint, OneDrive and Copilot connectors. That approach avoids separately copying or re-indexing those supported sources for that retrieval path. Glean describes connectors feeding an index and knowledge graph, alongside live-fetch and hybrid patterns. These are examples, not a full market survey or a performance ranking.
| Comparison point | Microsoft 365-centered approach | Glean approach |
|---|---|---|
| Documented retrieval model | Copilot connectors support search and agent knowledge; the Retrieval API retrieves in place from SharePoint, OneDrive and Copilot connectors. | Connector-fed search index and knowledge graph, with indexed, live and hybrid access patterns. |
| Published connector count | Microsoft Learn’s Copilot Search FAQ reports more than 100 Copilot connectors; the page does not state the count’s year. It is a vendor-published count. | Glean’s Agent Governance page reports more than 275 app connectors; the page does not state the count’s year. It is a vendor-published count. |
| Permission behavior described | Microsoft says SharePoint agent responses depend on each user’s permissions to the agent’s data sources. | Glean documents synchronized source permissions, subject to connector support and correct configuration. |
| Pricing detail established here | Microsoft says Copilot Search is included with a Microsoft Copilot license; some advanced connector functions may add cost or require separate licensing. Retrieval API licensing and preview consumption terms are described separately. | Specific pricing is not stated on the cited Glean pages. |
| Independent comparative performance evidence | Not stated in the reviewed vendor materials; the connector counts and architecture descriptions do not establish comparative answer quality, security or ROI. | |
Use this comparison to formulate tests, not to declare a winner. For either architecture, ask how quickly changed or deleted content becomes unavailable, which metadata and filters are supported, whether citations identify the retrieved source, and what the agent does when a source cannot be reached. A live query, an index and a hybrid model each create different dependencies; the relevant question is whether those dependencies meet your freshness, coverage and operational requirements.
Make permission enforcement a pass-or-fail requirement
Permission-aware answers are a security gate. Microsoft’s access-management documentation says SharePoint agent responses depend on each user’s permissions to the agent’s data sources, and inaccessible source content should not contribute to that user’s answer. Glean documents synchronized permissions, but says behavior depends on connector support and correct configuration. Validate the behavior in your actual tenant and connected systems rather than treating a product statement as proof of your deployment’s configuration.
Ask vendors to explain whether retrieval occurs in the user’s identity, mirrors source access-control lists, or uses a service identity with separate policy enforcement. Then test with real permission patterns. An agent should not quote, summarize or act on information a user cannot access in its source system.
- Test direct and inherited permissions, including access granted through groups.
- Change group membership and revoke access, then measure when the agent stops returning the item.
- Include guests, restricted sites and users with different roles.
- Try questions whose answers combine accessible and inaccessible documents; verify that restricted content does not leak through a summary or citation.
- Check behavior when a connector cannot represent a source’s permission model, including whether the source is excluded, broadly exposed or flagged for administrator action.
Run these tests both before launch and after changes to connectors, identity configuration or source permissions. Record the user identity, source item, expected access and observed answer so failures can be reproduced and fixed.
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Retrieval design is an operational trade-off, not a shortcut to a quality verdict. Ask vendors and administrators to demonstrate how the platform handles a recently edited document, a deleted document, conflicting guidance and content that is present but outside the user’s scope. Test filters for source, location, date, content type and sensitivity where they matter to your workflows.
For every representative question, verify that the retrieved evidence actually supports the answer. A useful citation should take a user to the source and relevant material, not merely name a system. Decide how the agent should respond when it finds no evidence, finds conflicting versions, or cannot retrieve a source. Prefer an explicit uncertainty or escalation path to a confident answer unsupported by available content.
Microsoft’s agent guidance recommends comparing answers with and without knowledge sources, and testing irrelevant and edge questions. Apply that method to a fixed set of questions with known source documents, including questions that should not be answerable. Track grounded-answer rate, citation correctness, retrieval coverage, latency, permission failures, action error rate and user effort. No independent cross-vendor benchmark or named buyer outcome statistic was established in the reviewed material, so a vendor’s architecture description should not be treated as a comparative benchmark.
Govern agents and connectors across every surface
Governance is more than a publish button. Before rollout, determine how administrators discover agents and connectors, approve them, restrict access, review activity, and disable them. Check agent sharing and publication, auditability, data loss prevention, retention, data residency, model-provider handling, incident response and shutdown procedures against your organization’s requirements.
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Also establish who owns connector approval, permission changes, incident triage and periodic access reviews. A platform’s controls matter only if the organization can operate them consistently across connected systems and agent experiences.
Separate read access from actions that change data
Begin with read-only retrieval and add actions only when they deliver clear value. Search and summarization expose information; a write tool can change records or send information outside the conversation. Treat those capabilities as different risk classes.
- Inventory each action: name the tool, credential, destination and data it can read or change.
- Apply least privilege: constrain the identity and scope to the minimum needed, and separate read capabilities from write capabilities where possible.
- Classify consequences: distinguish reversible changes from consequential operations such as external communications, approvals or changes to important records.
- Set approval requirements: require human confirmation for consequential operations and test both the confirmation and denial paths.
- Review evidence: retain and inspect logs that show the request, action, result and relevant approval.
Microsoft’s agent guidance calls for identifying actions that write or change external data and carefully governing sensitive actions, including human intervention where appropriate. Glean documents administrator control over tool availability and whether configured write tools run automatically or require approval. In either case, verify the actual tool configuration and logs rather than assuming the default behavior is safe for your workflow.
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Run a representative pilot with defined acceptance criteria
A pilot should test the conditions that can make an apparently good demo unsafe or unhelpful. Select real questions and known source documents across the repositories in scope, then test as users with different permissions. Include ordinary, edge, irrelevant and unanswerable questions, plus stale and conflicting content. If the agent can take action, include successful, denied and interrupted confirmation flows.
Best Value
Set thresholds before the pilot for task completion, grounded answers, citation correctness, retrieval coverage, latency, permission failures, action errors and user effort. Define how each measure is calculated, what counts as a failure and who can accept residual risk. Keep a record of expected evidence, retrieved sources, user identity and observed outcome for each test.
Expand testing across the applications where the agent will be available; behavior and controls may differ by surface. A pilot is not complete just because a few questions produce plausible answers. It should show that users get useful, verifiable information without exceeding their access, and that actions behave as intended when users approve, deny or abandon them.
Calculate total cost and migration exposure
Compare the whole operating model, not just a subscription line. Include licenses, connector charges or capacity, implementation, identity integration, content cleanup, connector administration, agent governance, evaluation and ongoing support. Also estimate the work and risk involved if you later change the retrieval layer, migrate configuration or replace a connector.
Microsoft’s Copilot Search FAQ says Copilot Search is included with a Microsoft Copilot license, while some advanced connector capabilities may add cost or need separate licensing. Microsoft’s Retrieval API documentation says the API is available at no extra cost with the Copilot add-on license and describes pay-as-you-go consumption as a preview for some cases. These terms can vary by capability and change over time; confirm the current geography, license, capacity and contract terms directly with the vendor. Specific contract pricing was not established here.
Connector counts are similarly time-sensitive. The figures above are vendor-published counts from pages that do not state the count year; recheck them during procurement. Neither count establishes that the apps, metadata, permissions or update behavior your organization needs are supported.
Choose by evidence from your environment
Favor the platform that passes your source-coverage and permission tests, meets your freshness and provenance needs, offers controls that administrators can enforce across the agent’s surfaces, and fits the workflows you intend to automate. Treat Microsoft’s and Glean’s documented capabilities as starting points for verification, not as proof of an outcome. The decisive evidence is a repeatable pilot using your sources, identities, questions and action boundaries, followed by a cost model that includes the work of keeping the system governed.
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