Organisations have access to increasing amounts of information. Most of this information is not stored in neat databases but instead is unstructured and sits in documents, spreadsheets, presentations, PDFs and web pages.
We have all become used to having very powerful search tools for online content but very few of us get that experience when looking at our internal documents. That usually stems from the lack of good search tools and holding our data in disparate places within the organisation. We can waste nearly 20% of our day looking for documents (source: McKinsey 2012-The social economy: Unlocking value and productivity through social technologies).
Symilarity’s Insight Engine can help address these issues by providing AI/Machine Learning powered search and enrichment tools and a simple set of repositories to hold data that needs to be available for search. It has a wide range of uses, from providing improved document search, matching tender opportunities to potential bidders, automated classification of businesses based on their website content and researching large quantities of academic papers.
How do we do that?
We upload the documents and ingest them, creating indexes that enable them to be searchable, even if there are millions of them.
Extract & Enrich.
We process the data using machine learning technologies. We extract information such as place names, or references to people or organisations. We can also add information, such as the key topics in the data.
We use the words contained in each document to learn how those words are related. This “unsupervised machine learning” process helps us find documents, even if the documents do not contain the specific search term you were using.
We provide powerful search technology, in a simple to use format, enabling you to search across all your data. We can also search for related data based on place names contained in the document.