Your Guide to Enterprise Search Software in 2025

In the time it takes to search through a mountain of data, files, and documents on outdated, keyword-based enterprise search software, your team could be getting more done. Search software is only effective if it actually helps your people find what they’re looking for. And the limitations of traditional enterprise search software have made this difficult.

Now, however, AI and machine learning have revolutionized enterprise search software. Contextual intelligence ensures search results are relevant, summarized, and delivered within workflows, making institutional knowledge more accessible and actionable.

We’ll explore some of the top AI search tools in 2025, with tips for choosing the right solution for you.

Eight top enterprise search software solutions in 2025

Enterprise search is one of the top use cases for AI, according to Menlo Ventures, with 28% of organizations investing in it. Businesses have a lot of solutions to choose from, but some are standouts in terms of efficiency, collaboration, and ROI. Here’s a list of some of the top enterprise search tools in 2025 to help you choose the right one for your needs.

The following list is curated from G2, which scores software based on user feedback, features available, and overall satisfaction. G2 uses a five-star system focused on usability, customer satisfaction, and market presence. Each of the tools listed here has a minimum rating of four stars, ensuring they are top contenders for streamlining your knowledge management process, improving collaboration, and helping your team work smarter.

1. Enterprise Search for Slack

Slack’s new enterprise search feature lets users search for key company information without ever leaving their work OS. Enterprise search builds on Slack’s powerful conversational AI search experience, allowing teams to connect all their third-party apps and drives to Slack to create a central, searchable hub for all their company’s knowledge and data. Find anything and everything you need instantly—from files and documents to conversational data and insights—all from Slack’s central search bar.

AI-powered enterprise search highlights the context behind users’’ queries and surfaces relevant answers in both a list of results and an AI summary. Thanks to a convenient preview in Slack, users can reference results without breaking their flow of work.

2. Elastic Enterprise Search

Elastic Enterprise Search is an open-source search and analytics engine you can use to create custom search experiences for your organization or customers. This flexible tool kit gives developers a way to build AI-powered search applications with an extensible platform that also comes with out-of-the-box capabilities.

The platform features a “relevance engine” that enables AI-based semantic search, as well integrations with third-party large language models (LLMs). It’s an ideal choice for storing, analyzing, and searching high volumes of data at scale.

3. Coveo

Coveo provides both customer-facing and internal AI-enabled enterprise search. Its features include generative answers, semantic search for better query-intent understanding, and personalized results that analyze user behavior.

Organizations use Coveo’s external features for things like ecommerce sites and service applications. Internally, it can serve as a traditional search engine as well as a tool for creating employee intranets. Coveo also integrates with various apps central to day-to-day business such as Zendesk, Salesforce, and Shopify.

4. Algolia

Algolia is a search platform that integrates easily with CMS platforms like Salesforce and Shopify. It combines semantic search with keyword matching to surface highly relevant results.

Other key features include intuitive filtering and sorting so users can customize results and AI capabilities that boost popular content and personalized suggestions. These features make it particularly useful for promoting content on customer-facing websites or mobile apps.

5. Sinequa

Sinequa uses deep learning to refine AI’s understanding of queries over time, gradually improving the quality of its search results. This software solution integrates with at least 200 enterprise apps and is designed to connect all your text and data content, interpret its meaning, learn from user interactions, and present information in relevant context. Sinequa is an ideal choice for large enterprises with high volumes of disparate data.

6. Glean

Glean uses AI and machine learning to deliver personalized search results based on user behavior and contextual insights. It surfaces this data in a user-friendly unified search hub. The Glean platform can draw data from over 100 apps, including Slack, GitHub, Jira, and more. Important for any enterprise-grade platform processing high volumes of information, Glean’s strong data protection features help prevent overexposure to keep data secure.

7. Guru

Guru is an internal knowledge management system that combines enterprise search with intranet and wiki features. It pulls from several existing data stores, such as Google Drive and OneDrive, and offers a Slack integration that enables users to easily access knowledge without leaving their work OS.

The platform’s visually organized knowledge cards and periodic verification reminders simplify the process of building a comprehensive knowledge database. Meanwhile, its semantic search capabilities and user behavior analysis guarantee accurate and relevant results.

8. AlphaSense

AlphaSense is unique in that it searches enterprise data and external information at the same time. This makes it a particularly useful tool for comparing outside sources such as financial research, market analysis, or trade news to internal documentation.

AlphaSense’s AI-powered search extracts key information from text-heavy resources to help users zero in on the news most relevant to them. Users can also set custom alerts for topics of interest and establish workflows within the platform.

Key features to look for in enterprise search solutions

Enterprise search software is much more than an organization’s internal search engine. The most effective enterprise search solutions are also AI-powered productivity and knowledge management tools that centralize data and streamline workflows.

Consider the following enterprise search capabilities when choosing your solution:

• AI-powered search. Leading enterprise search solutions will use natural language processing or LLMs to retrieve relevant information faster. Look for an AI solution with features like generative answers, semantic search, behavioral analysis, and machine learning or deep learning capabilities.
• Federated search. When search engines query multiple data sources at a time, as opposed to aggregating data in one location, it’s called federated search. This makes real-time indexing, or accessing up-to-date information the moment it’s saved, possible.
• Security and access control. With user access permissions, you control who’s able to see specific data. Your search software solution should also have strict security protocols that prevent unnecessary data sharing and uphold your company compliance policies.
• Integrations with business software. To avoid data silos and time wasted searching through various apps, your solution should connect with the tools you use every day. Choose software with a robust integration library that includes everything you need to index and search.
• Intranet features. Certain enterprise search tools also provide the ability to bring unstructured data sources together into a centralized intranet or employee wiki. If this resource is valuable to your organization, it may be something to prioritize when assessing enterprise search tools.
• Analytics and business insights. Many enterprise search solutions provide analytics for search terms and how information is being used. This can help companies make smarter decisions about how they manage their internal data.

 

A beginner’s guide to choosing enterprise search software

With so many enterprise search platforms on the market, choosing the right solution will depend on having a clear picture of your business needs and goals. From there, you can narrow your choice down to the best options.

Follow these steps to zero in on the right enterprise search platform for your organization.

Step 1: Identify your organization’s search needs

First, list your goals for implementing enterprise search software at your company. Does it need to be able to connect to large databases or to a handful of specific apps (or both)? What level of security do you need? Which types of AI will benefit your users the most?

You may want to survey users across several departments to get a clearer picture of how they would likely use enterprise search and which pain points they’d like an enterprise search solution to solve. For example, if users are tired of having to use exact keyword phrases to locate certain items, prioritize a solution with conversational AI search.

Step 2: Define search requirements

Once you have your goals and needs defined, you can get more granular when thinking about the search process itself. Consider the data sources you want your search solution to pull from and how best to organize that data. Also consider how search results will be able to integrate with your current platforms and workflows to keep context switching to a minimum.

Step 3: Assess AI and machine learning capabilities

Almost every enterprise search tool available today comes with some AI functionality, but not all solutions include the same tools. How each solution uses AI and machine learning will typically be the platforms’ key differentiator.

Reflect on your specific needs and goals to determine which AI tools can best support you. For example, if AI summarization is important to users at your organization, look for tools that support this function. Ask vendors for product demos to understand how AI search tools work and verify their accuracy.

Step 4: Ensure scalability and integration

Ideally, your enterprise search solution will support you as your organization grows. When considering your options, pay attention to all available integrations to make sure they’ll work with your current software and any potential tools you might adopt in the future. As your company grows, you also need a solution that can handle a high volume of data storage with minimal friction or downtime.

Step 5: Review security and compliance

Carefully review the security and compliance policies of each potential vendor. Prioritize vendors with third-party security certifications who can provide detailed documentation on how their product keeps your data safe.

Also think about your own approach to data security and make sure your new enterprise search tool can enforce your existing access controls and data protection policies.

Step 6: Conduct a cost-benefit analysis

Once you’ve narrowed down your list to a handful of vendors, the next step is to conduct a cost-benefit analysis to help you make your final choice.

Evaluate the total cost of ownership for each solution you’re considering, and compare that with the estimated benefits expected from the tool’s efficiency and productivity improvements. The right solution for you will be the one that promises the highest return on investment.

Enterprise search for interconnected businesses

Modern businesses manage vast amounts of data and resources, and they also must be able to access this information instantly to remain efficient and productive. AI-powered enterprise search software can streamline knowledge management and sharing across your organization without breaking the flow of work. This helps teams collaborate more effectively internally and make better decisions—and it can improve customer service workflows for higher customer satisfaction.

Enterprise search in Slack unlocks your organization’s collective knowledge, empowering employees across every department to find the information they need, when they need it, right where they’re working. With search across customer data, connected apps, and conversations, everyone can uncover critical insights, take action, and feed data back into business systems.