Institutions and organizations are inundated with text files, tables and lots of unstructured data. Information exists within organizations in emails, PDF documents, word files, Google docs, excels, structured relational databases and non-relational databases. If only it was easy to organize all this information and find the right answer to your question or query.
Our goal with SQUARE - “Scalable Question Answering Reference Engine” is to do exactly that. Based on your question, find the best answers and point you to the right source document quickly.
Our data scientists and product managers under the able leadership of my co-founder Dr. Eric Nyberg have been working on Natural Language Processing (NLP) techniques for a couple of decades to refine our modeling techniques and abilities to bring the best possible answer to you. We have utilized years of research and our experience with Kroll, Society of Automotive Engineers (SAE), Odds on Compliance, Iconekta, Schneider Downs and Solvaire to present an intuitive and very easy to use interface to answer your questions from your corpus of documents and your databases. In some cases we are the engine that powers their solutions via API calls and related interfaces.
Our SQUARE team comprises of world class researchers, data scientists and product managers. They have been looking at QA problems for over two decades for various organization types. Now we have a solution which we can deploy quickly with very high accuracy.
SQUARE is an end-to-end platform that automates manually searching information from unstructured documents, URLs, and relational databases (structured data).
Digitalization advancements led to a rapid increase in information storage of structured data like relational databases and unstructured data like documents, images, videos, etc. However, manually searching for information in this data storage is tedious and time-consuming.
Within a few seconds, SQUARE offers you the answers to all your questions, be it from local files or a domain-specific repository. Let us help you find that “needle in the haystack.”
The diagram below shows the working of SQUARE. The user utilizes a simple interface to present their query. In the background SQUARE has already organized all the documents and databases to be able to answer your questions correctly and efficiently.
See SQUARE in action for the Legal Services industry:
SQUARE can be utilized by the following entity types to find answers to your questions/search terms in large text documents, or any urls or databases on the fly.
Key to success is to demonstrate business value and ROI. SQUARE has already proven itself to demonstrate value in the following areas.
Please note that it is important to build ROI measures into your SQUARE implementation and operations from the beginning. It is equally critical to be able to report on them and learn from them for ongoing improvements and continued executive sponsorship.
SQUARE is easy to deploy and integrate. In its simplest form it is hosted on AWS and you can drop all your documents on an S3 bucket. Utilizing DIP it sorts, organizes, clusters, annotates your documents and databases. All you need to do is ask it your question on a very simple interface like Google. It can also integrate with your existing systems via API calls.
To get started and learn more about SQUARE please reach out to Jagriti Pandey at Jagriti@Cognistx.com and we can get a conversation started!