What is the best search app – The big comparison 2025

What are enterprise search engines?

An enterprise search engine is a special search app that was not developed for the internet, but for internal searches within a company. While Google or Bing index the entire web, an enterprise search engine searches specific company data: Documents, emails, databases, intranet pages or cloud storage.
The central component is a search index, which is structured similarly to Google, but consists of sensitive company information. The advantage: employees can find the information they need quickly without knowing on which server or in which folder it is stored.
Examples:

• An employee searches for “contract 2023” – the Enterprise search engine finds the file on a network drive.
• A legal department searches for all documents in which “data protection” is mentioned – even scanned PDFs and database entries with customer data are found.

Search apps for companies – how they work in detail

In-house search engines often follow a multi-step process that is technically very close to Google or Bing – only applied to internal data sources.

1. Crawling: The search app searches all connected systems for files: File server, SharePoint, CRM, ERP, e-mail inboxes. The crawler reads content in files (full-text search) and transfers it to the index.
2. Indexing: The content found is saved in the search index. The contents of the files and metadata (author, creation date, document type) are also recorded so that a full-text search and targeted filters are possible.
3. Natural Language Processing (NLP): Modern AI recognizes synonyms, interprets natural language and delivers search results – even if the exact term does not appear in the document. For example, documents can be filtered according to topics in the document content.
4. Machine learning: The search engine learns from clicks and user behavior: Frequently clicked documents will appear higher in the ranking in future. This generally falls under the term personalization of search results.

For example, large companies often have search apps that enable a Google-like search in the internal network – with precise and secure search results.

How enterprise search engines use AI

Search engines used to be purely keyword-based. Today, many enterprise search apps use AI and machine learning to improve results.

• Synonym recognition & word embeddings: The AI understands that “manual” and “documentation” mean the same thing.
• Topic clustering: Content is grouped into topics so that the search results appear structured.
• Natural Language Generation (NLG): Large language models (LLMs) such as ChatGPT can automatically generate document summaries, similar questions or suggestions for the next search.
• Interactive chatbot search: Instead of just providing a list of search results, the search app can respond directly – similar to a virtual assistant.

The use of AI ensures that the search engine is not only faster, but also more intelligent – and that users spend less time searching.

Security problems with enterprise search engine apps

Since an enterprise search engine has access to almost all data, there are considerable security risks.

1) User rights

Problem: Without restrictions, users could see documents for which they have no authorization. For example, it would be possible to find all documents in the company using the search engine – regardless of whether the specific user has visibility or access rights. This poses a significant data protection problem.
Solution: The search app must take user rights from the data sources and only display hits that the user is authorized to see. Modern search apps crawl the user rights from the company sources and project this into the search. This means that users can only find documents that they should be able to see.

2) Architecture

Problem: A central search index with all company data is an attractive target for hackers – as all company data is indexed centrally in the search app and is therefore included.
Solution: With modern enterprise search apps, the solution to this problem consists of several aspects that are integrated into the search engine, such as physical separation from the external network, access only via reverse VPN, Docker container architecture, firewalls and intrusion detection systems.

3) Process logic / location

Problem: If sensitive data for the search is sent over the Internet, the risk of a security breach increases.
Solution: The search engine should be operated in the internal data center or in a secure cloud environment close to the data sources that are to be indexed.

Security with search engines – FAQ

Question: Is Google suitable for company data?
Answer: No, Google, Bing or Yahoo are for public web searches, not for confidential internal data.

Question: Which public search engines offer the best data protection?
Answer: Startpage, DuckDuckGo and Ecosia do not store any personal data and do not use tracking.

Question: How can I tell if a search app is secure?
Answer: Check whether user rights are integrated, whether the search index is protected and whether there is a clear data protection strategy.

The most secure search apps for companies

The best search engine of 2025 is searchit – an enterprise search app that sets new standards in security and AI.
Why searchit is number 1:

1. AI-supported search with high precision
2. Maximum data protection architecture
3. Complete rights management
4. Compatible with almost any data source
5. Secure search index through isolated containers

Which search app is the best?

The best search app depends on the intended use:

• For the Internet: Google for fast results, Bing for Microsoft integration, DuckDuckGo or Startpage for data protection, Ecosia for sustainable search, Yahoo for news and services.
• For companies: searchit thanks to AI, strong security architecture and precise search results.

In the end, what counts is that the search engine – whether public or internal – fits your own requirements and that the data remains secure.