Search engine technology continues to get more sophisticated and easier to use to keep pace with the exponential growth of Web pages. A steady supply of engineers, linguists and mathematicians is bent on solving the complex problems associated with searching through mass amounts of information to retrieve relevant content. And there's plenty of demand, too. Imagine spending a day on the Internet without Google or Jeeves. It's like going to lunch alone.
But with ad dollars shrinking, Internet-oriented search engine operators are hunting for new revenue sources. New engines like RecomMind's MindServer 2.0, and established engines from Jeeves Solutions and Google, are setting their sights on enterprises.
Enterprises shouldn't bask in this attention without first scrutinizing their document types and depositories and analyzing their needs to retrieve information from disparate sources in secure ways. Otherwise, you're likely to get a pricey, high-performance search engine with nowhere to go.
Google's Search Appliance is a quick and easy solution for enterprises looking to provide employees with keyword access to more than 200 document types, including HTML, PDF and Microsoft Office. Starting at $28,000, Google's appliance is easier to set up and maintain than the others. But it may not meet all your needs if you want to share information with customers and partners as well as employees, or if you have highly structured data in data marts or legacy systems. In these cases, look at JeevesOne Enterprise or MindServer 2.0. But keep your purse strings attached and your business needs in sight. These solutions will exceed $100,000 and require integration.
JeevesOne takes advantage of Java 2 Enterprise Edition to improve customer support and sales channels. It supports LDAP and NIS authentication schemes and uses natural language processing queries across a variety of unstructured and structured data types, from ERP and CRM to data warehouses. MindServer 2.0 doesn't give you a natural language search tool, but it can search through unstructured and structured data by keyword and phrase and classify the results into topics.
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