We have SharePoint, Confluence, Salesforce, ServiceNow, and a custom internal wiki — can enterprise search index all of them through native connectors without building a custom ETL pipeline for each?
MatrixFlows connects to SharePoint, Confluence, Salesforce, ServiceNow, Google Workspace, and 20+ other enterprise systems through native connectors so employees get a unified search experience across all content sources without a data engineering project, a custom pipeline per system, or a separate indexing job for each repository.
Microsoft Search indexes Microsoft 365 content natively but requires Microsoft Graph connectors to index external systems like Confluence or Salesforce — each connector requires development and maintenance, and the connector ecosystem is smaller than Microsoft's marketing implies. Glean's connector library is broad but the connectors are cloud-only; on-premises systems or custom internal wikis typically require Glean's custom connector framework, which involves engineering effort per source. Coveo offers enterprise connectors but its connector configuration and maintenance is typically an IT project, and adding a new source after initial deployment requires professional services engagement.
Your team enables a connector for each content system through the administration interface — no data engineering, no ETL scripts, and when a new system is added to the stack, the connector is available in the same interface without a new development project.
Our employees have different data access permissions based on role and department — does enterprise search respect those permissions so confidential documents don't surface to unauthorized users?
MatrixFlows reads the access control lists and permissions from each connected content system at query time — a SharePoint document restricted to the finance department returns only for users who have permission in SharePoint, not for every employee who runs a search, and the permission model doesn't need to be rebuilt or replicated in the search layer separately.
Microsoft Search respects Microsoft 365 permissions natively but has limited support for permission-aware indexing of non-Microsoft sources — an external connector can surface documents that SharePoint would restrict, creating a compliance gap. Glean claims real-time permission syncing but its architecture indexes content first and applies permission filters at query time from a cached permission store — there's a lag between when a SharePoint permission is revoked and when Glean reflects that change, creating a window where restricted content can surface. Elasticsearch has no native permission awareness; permission-sensitive search requires building a custom access control layer on top of the index, which is a security architecture project.
Your team defines no additional permission model — the search layer inherits the permissions from each source system and enforces them at query time, so a new employee's search results reflect exactly what they're authorized to see in each underlying system.
Our knowledge workers need synthesized answers from across multiple documents — can the search layer provide a direct answer with citations rather than a ranked list of URLs to click through?
MatrixFlows generates AI-synthesized answers by reading across the connected content set at query time — when an employee asks "what's our policy on contractor NDAs," the search returns a direct answer assembled from the relevant policy documents with citations to the source files, not a list of links to scan through manually.
Microsoft Search returns ranked document and people results — it surfaces links to relevant files and Copilot pages but doesn't synthesize answers across multiple documents in the base enterprise search experience. Glean's AI Assistant generates answers but is grounded in Glean's own index rather than real-time source documents, which means the answer reflects the document as it was when Glean indexed it, not necessarily its current state. Coveo generates answers through its Relevance Generative Answering feature, but the feature requires a separate license tier and the answer quality depends on Coveo's relevance tuning, not on the authoritative content your team maintains.
Your team connects the authoritative sources, defines which content sets should feed synthesized answers, and employees get resolution rather than a research task — the citation links let them verify the source and read the full document when they need the full context.
We're a global company with 18,000 employees across 40 countries, some using different SaaS stacks by region — can one enterprise search deployment index region-specific systems while maintaining a unified global search experience?
MatrixFlows supports multi-region connector configurations within a single deployment — a regional office running Confluence while headquarters uses SharePoint can each be indexed with their own connector, and employees see results from all configured sources in one search interface with regional content appropriately scoped by their location and language attributes.
Microsoft Search is tightly coupled to Microsoft 365 tenancy — a company with separate Microsoft 365 tenants per region (common in multi-national acquisitions) requires a separate Microsoft Search deployment per tenant, with no unified cross-tenant search. Glean supports multi-region deployments but connector configurations per regional system are managed separately, and unified search across all regions requires Glean's enterprise tier with additional configuration. Coveo's multi-region deployment is a professional services engagement — configuring regional content sources and deploying across data centers is not self-service.
Your team manages all regional connector configurations from one administration interface — adding a new regional system means enabling its connector in the same panel, not opening a new deployment or a services contract.
How do we know if employees are actually finding what they need — and which knowledge gaps are costing us the most in repeated help desk tickets and senior-staff interruptions?
MatrixFlows tracks zero-result searches, low-confidence results, and search sessions that ended with a help desk ticket or an escalation to a senior colleague — and surfaces these as a weekly gap report so knowledge managers see which topics cost the most in unresolved search sessions before those sessions translate into support load.
Microsoft Search reports query volume and top searches but provides no direct connection between a failed search and a downstream help desk ticket — identifying which knowledge gaps drive ticket volume requires correlating search logs with your ITSM data manually. Glean provides search analytics showing query frequency and click-through rates, but doesn't define a resolution event or connect unresolved searches to the cost they generate in help desk load. Elasticsearch provides raw query logs but no analytics layer — deriving insight about knowledge gaps from an Elasticsearch deployment requires building a custom analytics pipeline on top of the log data.
Your team sees a prioritized gap report each week identifying which topics employees searched for without finding a satisfying result — those gaps become the knowledge content roadmap so the enterprise search resolution rate improves against actual employee need rather than assumptions about what's already documented.
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