The Four Types of Enterprise Search Platforms and Intranet Search Engines

Digital Transformation , Digital Workplace , Enterprise Search , Intranet

The Four Types of Enterprise Search Platforms and Intranet Search Engines

Intranet search engines and enterprise search apps come in many shapes and size. Here’s the rundown.

byAndy Wibbels on June 3, 2020

A couple weeks back we talked about the nightmare hellscape that is terrible enterprise search. Then last week, we laid out the path to something much better.

This I wanted to take a quick taxonomy of the enteprise search market consists of leading vendors, cloud solutions, legacy solutions, application-specific search and open-source toolkits.

Comprehensive platformslike Lucidworks Fusion allow for cloud, on-premises and hybrid installations. These platforms lead the way in personalization and machine learning technologies that come as part of a complete solution, including A/B testing as well as user and operational monitoring. These solutions cover a complete set of search needs, including enterprise search, site search, ecommerce search, as well as customer and product 360.

Cloud solutionsmove operational concerns out of the purview of the customer and vary in comprehensiveness or specificity. Some of these solutions are quite complete, but many require additional systems for data ingestion or user profiling capabilities. Some of these solutions only search CRM tools or are limited to a small set of cloud-only sources. These are a great way to handle specific business problems and may offer a form-fit solution to a given organizational pain point.

Application-specificsearch includes the search built into services like SharePoint or Salesforce, but also includes third-party solutions such as Coveo or Attivio, which focus strictly on one or a limited set of data sources. Application vendors often do a poor job of providing search, and while third-party solutions can be helpful, application-specific search frequently misses the context and introduces inefficiency where a user has to search multiple systems to put together the “bigger picture” or find exactly what they were looking for. Smaller organizations generally rely on a set of application-specific search solutions. Legacy solutions include those from vendors that no longer exist like FAST or Verity. Some of these solutions are still offered from their acquiring vendor, but few have kept up with recent technology. This problem pervades the solution from providing poor search results, trouble connecting to new data sources, and not scaling for modern use. Most large organizations are replacing legacy solutions.

Open source toolkitslike Elasticsearch or Apache Solr are widely deployed. While Solr provides excellent scalability and performance, it doesn’t provide cutting edge machine learning and personalization features. It also requires a lot of custom scripts and operations in order to deploy and maintain effectively. While some of the largest search deployments in the world use Solr, these are primarily managed and developed by technology firms. Most larger enterprises want complete solutions that handle a variety of search and operational concerns and don’t want to have to develop it themselves.

While most search solutions fall into these categories, not all are created equal. Key differentiators include their core architecture and how scalable the solution is. Additionally, some vendors are spending a lot of R&D on personalization and AI technologies, while others are moving to specialize more in specific areas of domain search (i.e. CRM search or log analysis).

Let’s Get Going

It’s time to replace hit-or-miss search with an all-in-one answer platform for data diggers, fact finders, and edge seekers everywhere. More than anything, it’s time to find out what’s possible when employees have all the insights they need, whenever they need them.Contact us todayor use the form below.

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