Best Enterprise AI Search Tools

Glean is the best managed default for a company-wide employee-search rollout.

Its package combines broad connectors, permission-aware indexing, a knowledge graph, generated answers, and an opinionated user experience.

We would choose differently for a Microsoft-centered company, a developer platform, an external search product, or a self-managed stack.

We found no current controlled benchmark that tests these products on the same corpus and permission model. This is a fit ranking built from first-party product, pricing, and availability documentation. The buying process still needs a private retrieval evaluation.

The shortlist by operating model

Table 1 Download CSV

Product	Best fit	Pricing shape	Main limit to test
Glean	Managed employee search across many SaaS systems	Quote	Contract cost, connector depth, and admin control
Microsoft 365 Copilot	Microsoft 365 organizations	$30/user/month, annual, qualifying plan required	Coverage outside Microsoft Graph
Google Cloud Agent Search	Teams building search into apps	Queries, generation, and storage	Engineering and evaluation burden
Perplexity Enterprise	Web research plus connected company sources	Pro $40/user/month, Max $325/user/month	Internal-source governance and answer controls
Elastic	Search teams that want low-level control	Usage-based serverless or self-managed	Relevance engineering and operations
Coveo	Customer service, commerce, and knowledge search	Quote, entitlements vary by solution	Packaging complexity and query entitlements
Guru	Search plus verified knowledge workflows	Plans start at $25/seat/month	Knowledge-maintenance process fit
SearchBlox SearchAI	Fixed-cost cloud or on-prem search	Quote, fixed-cost positioning	Smaller ecosystem and implementation evidence

Amazon Q Business is absent from the recommended shortlist for new buyers. AWS documentation says the product stopped accepting new customers after July 31, 2026, existing customers can continue. New AWS-centric evaluations should start with Amazon Quick rather than assume an expiring entry path.

Glean is the managed default

Glean packages the pieces that usually become a program: connectors, real-time indexing, inherited permissions, semantic and keyword retrieval, a company knowledge graph, generated answers, and an employee-facing search experience. Its connector catalog lists more than 275 integrations.

That breadth reduces integration work, which is the main reason to shortlist Glean. A search engine can be technically strong and still fail because the organization cannot keep connectors, identities, permissions, and content freshness aligned.

The limit is commercial and operational visibility. Public pages do not give a simple seat price, and a connector count does not establish depth. In a trial, test the systems that carry the messiest permissions, not only Google Drive and Slack. Ask how deleted documents, group changes, shared links, and source outages propagate.

Glean wins when the organization wants one managed employee-search product and values implementation speed over infrastructure control.

Procurement should ask for a connector-level implementation plan, not a logo sheet. For each source, record supported objects, permission model, incremental update behavior, deletion handling, attachment extraction, historical backfill, expected indexing delay, and who owns failures. One deep connector to a critical system can be more valuable than fifty shallow ones.

Microsoft wins inside Microsoft 365

Microsoft 365 Copilot is the natural first test when SharePoint, Teams, Outlook, OneDrive, Word, and Entra already define the work graph. Microsoft lists the enterprise Copilot license at $30 per user per month on an annual commitment, with a qualifying Microsoft 365 plan required. Copilot Chat is included for eligible Entra users, agents can add metered charges.

The advantage is identity and application context. Users can ask questions where they already work, and administrators operate inside an existing security boundary.

The evaluation should focus outside that boundary. If product knowledge lives in Salesforce, Jira, Zendesk, engineering databases, or acquired-company tenants, measure the connector and permission behavior rather than assuming the Microsoft estate covers the company.

Google is a builder's search platform

Google Cloud Agent Search pricing is unusually explicit. Standard search costs $1.50 per 1,000 queries. Enterprise search, including core generative answers, costs $4 per 1,000 queries, advanced generative features add another $4 per 1,000. The service includes 10,000 queries monthly, and indexed storage is $5 per GB per month after the first 10 GB.

This is infrastructure for a product team, not a finished employee-search rollout. The value is control over data stores, schemas, ranking, interfaces, and application integration. The cost is that the buyer owns relevance evaluation, permission mapping, user experience, and ongoing tuning.

Choose it when search is a product capability and engineering control is worth more than a turnkey portal.

Perplexity is the research-first option

Perplexity Enterprise Pro lists $40 per seat monthly or $400 annually. Enterprise Max lists $325 monthly or $3,250 annually. The product begins with answer-oriented web research and adds enterprise controls and connected sources.

That makes it a strong fit for analysts, sales, strategy, and research teams that move between public and internal information. It is less obviously the company system of record for internal search than a platform built around enterprise indexing from the start.

Test citations that mix public and private evidence. Confirm whether the answer makes the boundary visible, how administrators control connectors, and what happens when internal evidence disagrees with a current public source.

Elastic is for teams that own relevance

Elastic provides the primitives for hybrid retrieval, vector search, ranking, observability, and custom interfaces. Its serverless search pricing meters ingest, search, and machine-learning compute separately. The current product guidance also matters: Elastic says the old standalone Enterprise Search, App Search, and Workplace Search packages are in maintenance mode and recommends Elasticsearch-native tools for new work.

That makes Elastic powerful and demanding. Search specialists can tune analyzers, fields, filters, rerankers, and retrieval pipelines around a specific corpus. A team expecting a polished employee-search portal on day one will have more work than with Glean or Microsoft.

Elastic wins when relevance is a product competency, not an outsourced feature.

Coveo and Guru solve narrower organizational problems

Coveo is strongest when search connects directly to customer service, commerce, websites, Salesforce, ServiceNow, or knowledge experiences. Its platform combines a unified index, machine-learned ranking, recommendations, and generated answers. Entitlements vary by platform and solution plan, so procurement should map query volume, indexed items, connectors, and user counts before comparing quotes.

Guru combines permission-aware search with knowledge verification. That second part matters when the problem is not only finding a document but deciding whether the answer is still approved. Guru advertises plans starting at $25 per seat monthly and custom enterprise terms.

Coveo fits search-led digital experiences. Guru fits teams willing to maintain a verified knowledge layer. Neither should be reduced to a generic Glean substitute.

SearchBlox pairs search with deployment control

SearchBlox SearchAI offers managed and self-managed deployment, hybrid retrieval, RAG, knowledge graphs, agents, and fixed-cost positioning rather than token or seat metering. Its Inception partnership report says Mercury is available as a model endpoint inside SearchAI.

The partnership report is not an independent latency benchmark. It does establish the integration and the intended architecture: SearchBlox handles indexing and retrieval, Mercury handles generated text. Buyers considering on-premises or private-cloud deployment should test this route alongside Elastic and custom stacks.

Run a permission-first evaluation

Use 100 to 300 real questions spanning easy lookup, synthesis, stale documents, conflicting sources, acronyms, and questions with no answer. For each query, record the expected source and which test users may see it.

Score at least these outcomes:

• retrieval recall for the expected evidence,
• citation support for every generated claim,
• permission leakage, with any leak treated as a release blocker,
• freshness after edits, deletions, and access changes,
• abstention when the corpus does not support an answer,
• administrator time to diagnose a miss,
• median and tail response latency, and
• total monthly cost at expected users, queries, and storage.

Do not let one polished demo choose the product. The hardest enterprise-search problem is not phrasing an answer. It is returning the right evidence to the right person after the source system changes at 4:17 p.m.

Run the trial long enough to observe those changes. A four-week evaluation can include group membership updates, policy edits, connector outages, source migrations, and an ordinary volume cycle. Require administrators to diagnose several planted failures without vendor guidance, then record the time and evidence available to them.

Price the evaluated configuration rather than the entry plan. Include implementation services, premium connectors, storage growth, query or generation overages, agent capacity, support tier, sandbox environments, retention, and the internal staff needed to operate the system. Divide the result by supported answers and completed workflows, not licensed seats alone.

Put the evidence and commercial assumptions in the durable decision memo. A successor team should be able to see which corpus was tested, which permissions were exercised, what the quote included, where the product failed, and which future change would justify reopening the choice later.

The best tool is the one that survives that change.