With Enterprise Search being a quickly growing enterprise software segment, a lot of people ask us at ambeRoad how enterprise search differentiates from web search. That’s why we have taken the time to outline the main technological differences.
The goal of both search engines is to search through huge amounts of data a human cannot overview anymore and then presenting the user the information in a simple way. In the front end the results usually look very similar. In the back end, however, one search engine searches webpages and can use millions of user interaction to analyse and rank its result, the other search engine must rank the documents right without millions of user data. Over the years Google, Bing & co have become so good at presenting us always the right piece of information even if we are unprecise with our search query that we cannot imagine a life without them anymore. However, this is purely based on web search engines using millions of user data sets to detect temporal and geopraphical trends
As the amount of data and documents, often described as the new gold of the 21st century, continues to grow exponentially companies realise that they will have to implement solutions to find information in their documents just like web search Engines enable you to find data in the web.
If Enterprise Search is such a big thing, why is Google not in the business, you may ask?
Think about it this way: Web search engines use the interactions of millions of users and the number of hyperlinks between websites to train their models and to rank the webpages. The information needed for web search is publicly available and in relatively similar data formats. Additionally, Google’s results are , for example, distorted due to ads within the results. Googles business model is based on the data you are willing to give them and then showing you the most relevant ad results and keeping you interacting as much as possible with their products to gather even more data.
Enterprise Search, on the other hand, has a lot of data sources like file servers, mail, Office365 etc with different data formats (such as ppt, XML, png, dwg) connected to it where years of company knowledge is stored. Furthermore, this information is not available to everyone within the organisation. Take for example an intern, who is not allowed to see the same documents as the director. In opposite to enterprise search, in web search, everyone is allowed to see everything. Ultimately, this makes Enterprise Search far more complex than Web Search. Additionally, the purpose of Enterprise Search is to keep the time you are spending on it as low as possible, so you can continue with value adding work instead of searching for information. The challenge for enterprise search providers is to find the right document purely based on its content and the information it contains as there are no large data sets with user data available. The Enterprise Search user nowadays expects to find the right piece of information, just like in Google or DuckDuckGo, even if he may only search for the information once a year.
Consequently, Enterprise Search providers must have very precise models and algorithms to provide that Google feeling to its customers. However, what is going on in the back end and the business models are something completely different to what web search engines use.
At ambeRoad, we realised that existing Enterprise Search engines are not able to provide the same feeling like web search engines as they cannot cope with the vast amounts of data available nowadays. That’s why we developed an intelligent Enterprise Search engine that lives up to that Google feeling within your company.
If you want to find out more about our approach then watch our video from our project with the RAG.