Enterprise AI Search Tools in 2026: 9 Platforms Compared on Connectors, Permissions and Hosting

What enterprise AI search does, and what to compare

Enterprise AI search combines three parts: connectors that crawl or query content in business systems, a retrieval layer that respects each source’s permissions, and a language model that turns retrieved passages into a cited answer. Most of the differences between products sit in the first two parts. These are the questions that separate them:

• Connectors. Vendor counts are marketing figures. Check the exact sources you need, whether each connector indexes content (synced) or queries it live (federated), and whether on-premises systems are reachable at all.
• Permission-aware results. Ask whether source access lists are synced, how often, and whether filtering happens at query time before anything reaches the model.
• Deployment. Multi-tenant SaaS, a single-tenant instance in your own cloud account, self-managed software, or a true on-premises install.
• Data residency. Which regions hold the index, the logs and the conversation history, and which model providers process the prompts.
• Pricing model. Per seat, per credit, per query or per capacity, and whether list prices are public.

Enterprise AI search platforms at a glance

Facts come from each vendor’s own pages and documentation, verified October 2026. Connector counts are the vendors’ own figures. A dash means the item was not published on the pages we checked.

Cloud search platforms

Glean

Glean connects to more than 275 apps through native, partner and custom connectors, and fetches each source’s permission map so results follow the access rules set in the source application. Changes arrive through webhooks or incremental crawls, and an Indexing API pushes content from systems a crawler cannot reach. Glean offers two deployment models: Glean Hosted, a single-tenant SaaS on Google Cloud, and Customer Hosted, previously called Cloud-Prem, which runs Glean as a managed service inside your own GCP or AWS account while Glean keeps support access. Neither is an install in your own data centre, and prices are quoted on request. Teams moving off Glean will find the self-hosted route in our overview of Glean alternatives.

Microsoft Copilot Search

Copilot Search is the Search module of the Microsoft Copilot app, which Microsoft renamed from the Microsoft 365 Copilot app. It requires an eligible Microsoft Copilot licence; unlicensed users keep the free, keyword-based Microsoft Search. External content arrives through Copilot connectors. Synced connectors index items into Microsoft Graph with an access control list on each, while federated connectors fetch data live through MCP without indexing it and are read-only for now. Microsoft lists over 100 prebuilt connectors, among them Confluence, ServiceNow, Salesforce, Jira and SAP, and its Graph connector agent indexes on-premises sources. Each connection carries an access setting, limited to people with access in the source or visible to everyone, so review it connector by connector.

Gemini Enterprise

Google’s employee-facing product is the Gemini Enterprise app, which its documentation describes as an intranet search, AI assistant and agentic platform. Google’s compliance page refers to “the Agentic AI Service formerly known as Agentspace” as part of the Standard and Plus editions. Prebuilt connectors cover Confluence, Jira, SharePoint and ServiceNow, and federated data stores for Jira Data Center, Confluence Data Center and ServiceNow reached general availability in June 2026. Results and generated answers are permissions-aware, and since 28 September 2026 administrators can set resource-level IAM permissions on individual apps and data stores. The Standard and Plus editions support data residency zones, customer-managed encryption keys in the US and EU multi-regions, and VPC Service Controls. Editions are sold per seat.

Atlassian Rovo

Rovo is included in Atlassian Cloud Standard, Premium and Enterprise plans for Jira, Confluence, Jira Service Management and the Teamwork and Service Collections, with a per-user monthly credit allowance pooled across the organisation; extra usage costs $0.01 per credit (list, verified October 2026). Rovo Search merges Atlassian content with third-party apps through three connector types: synced connectors index a whole workspace, direct connectors query providers such as Slack and Gmail live without storing content, and Smart Link connectors index only links users have already seen. Users connect their own third-party accounts so results stay within their existing access. Rovo data follows the data residency region of Jira or Confluence, and the full AI feature set needs Atlassian Cloud.

Amazon Quick, the successor to Amazon Q Business

Amazon Q Business is no longer open to new customers. AWS keeps shipping bug fixes and security updates for existing ones and recommends moving to Amazon Quick, which can connect an existing Q Business index during migration. Quick’s knowledge bases support document-level ACLs for Amazon S3, SharePoint, Confluence Cloud and Google Drive. The ACL choice has to be made when a knowledge base is created and cannot be changed afterwards, and for S3 knowledge bases with ACLs enabled, documents without an ACL entry are not ingested. Systems without a native integration can be reached through MCP for actions but not indexed. Professional lists at $20 and Enterprise at $40 per user per month, plus a $250 monthly infrastructure fee per account (verified October 2026), and only Enterprise users can configure integrations.

Coveo

Coveo runs as a multi-tenant SaaS platform on AWS with data centres in the United States, Canada, the European Union and Australia. At indexing time its crawlers store the users and groups allowed to see each item alongside the content, so results show only what a person may open in the source. Most connectors can replicate the original permission system; where one cannot, permissions are defined manually at source level. Generative answers are grounded in the indexed content. Coveo sells its workplace offering per seat and quotes prices on request.

Self-hosted and on-premises options

Onyx

Onyx is an open-source platform for chat and search over company knowledge. The Community Edition is MIT licensed, and an Enterprise Edition adds features aimed at larger organisations. It connects to more than 50 applications, works with self-hosted models served through Ollama, vLLM or LiteLLM as well as commercial APIs, and can run air-gapped with the index, database and processing inside one self-contained set of services on Docker or Kubernetes. Its documentation lists permission syncing, which mirrors source ACLs for Confluence, Jira, Google Drive, Slack, SharePoint and other sources, as an Enterprise Edition feature; without it, each connector is either private or public. The hosted Business plan lists at $20 per user per month billed annually (verified October 2026).

Elastic

Elastic is a search engine you build on rather than a finished employee app. More than 35 content connectors sync sources such as SharePoint, Confluence, Jira, Google Drive, Salesforce and ServiceNow into Elasticsearch, either self-managed on your infrastructure or managed by Elastic on its cloud. Document-level security stores the identities allowed to see each document and filters results at query time through API keys with role templates. Agent Builder, generally available from version 9.3 and on Serverless, adds chat and custom agents over your indices and can call local LLMs through connectors. The source code is available under AGPLv3, SSPL or the Elastic License 2.0, and Agent Builder needs an eligible subscription tier.

Sinequa

Sinequa, owned by ChapsVision since November 2024, is one of the few commercial platforms here sold for on-premises use: customers can deploy it in their own data centre, in a private cloud tenant or as Sinequa’s fully managed SaaS. It advertises connectivity to more than 200 data sources, inherits existing permissions through document-level security, and is LLM-agnostic, so organisations can bring their own models.

How permission-aware search actually works

All nine platforms use a variant of the same mechanism. Connectors read each item’s access list during a crawl and store it with the content, a separate sync keeps user and group memberships current, and every query is filtered against the user’s identity before passages reach the model. Three failure modes deserve a test in any pilot:

• Connectors that cannot read source permissions. Administrators then choose between broad visibility and manual source-level rules. Coveo documents this case, and Onyx connectors fall back to private or public when permission sync is unavailable.
• Settings fixed at setup. Amazon Quick decides ACL support when a knowledge base is created, so a wrong choice means rebuilding it.
• Sync lag. A revoked permission only takes effect after the next ACL sync. Ask how often group memberships and item ACLs refresh, and whether webhooks shorten the gap.

A simple test plan covers most of the risk. Seed a handful of restricted documents, query them from low-privilege test accounts, revoke a permission in the source mid-pilot, and time how long the answer takes to disappear. Our guide to permission-aware retrieval follows access controls from ingestion through reranking to citations.

Build vs buy: when private RAG is the better route

Buying makes sense when knowledge lives mostly in mainstream SaaS tools, cloud processing is acceptable, and connector breadth matters more than control over the index. Building on private RAG makes sense in three situations:

• Regulated content may not leave your infrastructure, and that includes the index and embeddings, which concentrate everything the company knows in one place.
• The important sources are file shares, on-premises wikis or internal databases that a cloud indexer cannot reach safely.
• Retrieval will feed agents that take actions, so it belongs inside the same governed perimeter as the agents.

Building is not free. You own the connectors and the ACL mapping, chunking, retrieval quality and ongoing evaluation. Two places to start are combining keyword and vector retrieval and a framework to measure retrieval accuracy before users notice the gaps.

How VDF AI fits

VDF AI sits on the build side of that decision as a packaged product. VDF AI Chat runs private RAG on infrastructure you control, on-premises, in a sovereign cloud region or air-gapped. Its connectors for Confluence, Jira, GitHub, SharePoint and OneDrive, Google Drive, Notion and Fireflies.ai carry each source’s access lists into the index, and every query is filtered against the requesting user’s identity before candidate chunks are scored. Sources are re-crawled on a schedule and on webhook events, so permission changes propagate.

Each turn writes an append-only record of the identity, the agent and model version, the retrieved chunks and any tool calls, exportable to your SIEM. For a ready-made agent, the enterprise search assistant answers across wikis, tickets and repositories with cited sources. The SaaS platforms above lead on connector breadth, so map your own systems against each option’s connector list before choosing.

Sources

• Glean connectors
• Glean connector documentation
• Glean deployment models
• Glean pricing
• Microsoft Copilot Search
• Copilot connectors overview
• Copilot connector access permissions
• Microsoft Copilot licence options
• Gemini Enterprise documentation
• Gemini Enterprise editions
• Gemini Enterprise compliance and security controls
• Gemini Enterprise release notes
• Rovo pricing
• Rovo Search
• Rovo connector types
• Rovo data use and residency
• Amazon Q Business availability change
• Amazon Quick pricing
• Coveo platform security
• Coveo content security
• Coveo pricing
• Onyx repository
• Onyx connectors and permission sync
• Onyx pricing
• Elastic content connectors
• Elastic document-level security for connectors
• Elastic Agent Builder
• Elastic licensing FAQ
• Sinequa platform
• ChapsVision acquisition of Sinequa