The move is testament to the new world of the enterprise, where platforms are an attractive option for building applications that leverage the Web and multiple forms of structured and and unstructured data. It's a world where a search app has to be simple to build and flexible enough to connect people to the right information, be it internal documents or social data from the distributed Web.
At its core, LucidWork Enterprise is built on the Apache Solr/Lucene platform. Layered into the thinking it is a realization that content is changing in multiple dimensions. In terms of volume, content is coming in at a new pace. Twitter is testament to the speed in which data is now flowing.
And with this volume, the semantics are changing, too. The challenge becomes how semantics are refined in a search environment.
Video search, for instance, has a different context than plaint text. How that data is transformed into a search environment becomes a matter of how the service is built in the first place. The issue becomes a question of definition about the content and its meaning.
But in the end, the user gets information in different ways. They may type a query and gets a result or they may have an automated search to get the information they need.
It has to be straightforward. That means the search has to be easy for the customer to integrate. LucidWorks Enterprise works on the premise that Solr/Lucene can be leveraged with APIs. Customers can build their applications based upon a common admin console where data can be added and search features tuned depending on the needs of their users.
APs provide benefits such as the arms length configuration of Solr. Developers do not have to edit a Solr config file. Setting up the system, supplying data and schedules can be done through the API.
A click scoring feature provides the capability to leverage how the user interact. Results can be prioritized based upon what the user has already selected. Alerts have also been added for when new information has been added to the index. The system provides real-time feedback for developers on data coming through the connectors.
Enterprise search is a different animal than its consumer counterparts. it needs customization and refinement to be useful. There are multiple options. Google Search Appliance, Microsoft FAST, Autonomy and Endeca all compete with Lucid.
Building search technology into applications makes sense in this changing world of big data. Search has to be easy to scale. Building applications on open-source and APIs may not be for everyone but it does allow for providing the end user with an environment
that can be fine tuned depending on the content being searched and its overall context.