Google intranet search appliance
In the beginning of this year Google launched search appliance search software that is designed for the intranet of small and medium businesses, some large corporations or a website. The end user functionalities are somewhat similar to the internet experience: Page summary, high ranking relevance quality, cache pages, an HTML view of more than 220 file types including most PC/MAC formats and many more.
The search product line by Google Is divided in three. Google mini is very limited but would be a smart more for SMB with a capacity up to 50,000 documents. The next model in the product line is the GB 1001 searches up to 1.5 million documents and allows 300 queries per minute. The GB 5005 is more powerful with an ultimate capacity of 3 million documents and is very well adapted to companies whose knowledge bases are critical to employees. While the top of the Google search appliance line is covering needs up to 15,000,000 documents including high end networking and security features.
Google is of course expecting a large number of demands for this product based on its incredible authority for internet search. The search engine company also has certain credibility in corporate governance and employee management; Google employees are treated like no others and for example are allowed to spend 20% of their time working on personal projects. Of course if something good comes out of these projects they will remain Google’s property but being able to manage so differently a so large company with so many critical amount of information and this high level of technology should help Google convince a large number of corporate prospects.
More recently Google bought Urchin, the web analytics software editor and this is a sign that the company is aiming at moving towards very serious businesses as clients. It is long gone the time when the search engine was just a university student project playing around between coding and algorithm. As far as SEO are concerned it would be nice to be able to reverse engineer the application just to find out if some similarities could be used to help ranking higher!
