They say that in the modern day data and information is currency. All the big companies believe in this and are investing big-time in analytics to distinguish between the data that is critical to their operations and those which are not. This kind of data intelligence is empowering today’s businesses by helping them gain insights into their businesses and the markets.
Although there are many companies offering analytics services, there are few which help solve complex and unstructured text challenges in real-time and at scale. Finch Computing, founded in 2014, is the best at this.
Originally founded as Synthos Technologies, the company rebranded itself as Finch Computing in 2015. Finch Computing started as a division of Qbase, LLC as its leadership thought that there was a space for a company which could focus on bringing new tools to market which would help customers move away from simply sifting through a lot of data – to – data that makes sense.
With the establishment of Finch Computing, Qbase products like their geo-intelligence solution, MetaCarta, Data Discovery, and Data Transformer tools became a part of Finch Computing.
Finch for Text
A lot of the information that requires analysis today is found to be in the textual form. The data that trickles in from various systems in a business setting varies. Sometimes, the textual data can be structured; in others, it could be unstructured. Moreover, one of the hardest things a machine can do is – try to understand and decipher the intent and the tone of statements which play a significant part in the human generated text.
Finch for Text is Finch Computing’s powerful analytics solution that is different. It uses natural language processing, machine learning, sophisticated statistical models and heuristics to extract the right data. Its ability to analyze is one of the best. The product is unlike others in its competition as it is able to extract, decipher entities and sentiments like no other solution in the market.
In 2017, Finch Computing performed an internal assessment that looked at its own Finch for Text solution and 14 other text analytics solutions covered in the press. The results showed that Finch for Text analytics had outperformed all of its competitors.
The human generated text is full of intent and emotions which are analyzed through certain keywords that other analytic solutions latch on. These render either a positive or negative sentiment to the whole document or resort to associating a particular sentiment to individual sentences in a text. But what if sentences consist of other sentiments such as angry, sad or happy? One of the stand-out features of the Finch for Text is that it does remarkably well in sentiment analysis which is one of the hardest text analytics functions to get right.
Finch for Text is different as it leverages the context-based approach by assigning sentiment to individual entities. This proves to be extremely valuable while examining transcribed customer service interactions or product reviews.
Finch for Text analytics solution by Finch Computing works on top of FinchDB. It is an in-memory, distributed JSON, doc database. Unlike other conventional databases, FinchDB combines a database with search and analytics capabilities onto a platform that is scalable. Its architecture and proprietary compression allow FinchDB to be very fast. It can handle more than 1,800 queries per second on a four-node computing cluster and process a single 3,000 character document in just 24.2 milliseconds.
Company with unique intellectual property
Finch Computing prides itself of having dozens of unique pieces of intellectual property to its name. This high number in its IP portfolio shows how transformative Finch Computing’s innovations have been in text analytics, knowledge discovery and data compression. The company continues to be a genuine leader which continues to explore new and better ways to analyze and understand textual information.
Steve Baldwin, CEO
Mr. Baldwin’s extensive 30 year career in technology has seen him successfully build IT companies. Prior to Finch Computing, he was the President and CEO of Apptis, Inc. He was pivotal in the company’s growth from an 18-man strong enterprise to a 1,600 employee workforce over a timeframe of ten years. His leadership helped the company garner a substantial market share in civil, healthcare and defense/national security segments.
Before Apptis, he was a partner at Concept Automation Inc. and was the General Manager at BTG. At BTG, he led the largest division and helped drive the revenue from $190 million to $450 million within two years.
-In 2016, Finch Computing’s entity extraction and disambiguation solution, Finch for Text, got four gold stars from the U.S. Department of Defense’s DI2E PlugFest. DI2E PlugFest is DOD’s annual event to demonstrate mission-furthering advancements in DI2E. Finch Computing got the gold stars for DI2E SVCV-4, DI2E Mash-Up Participant, DI2E Aligned and DI2E Cyber Awareness.
-Finch Computing was included in global research firm Gartner’s 2016 “Cool Vendors in In-Memory Computing” report.
“We have a massive knowledge base of people places and organizations and the ability to perform complex, accurate analytics on text.”
“Finch Computing provides customers with the ability to find hidden meaning and insight in huge volumes of data.”
“We use our unique intellectual property and knowledge assets to offer compelling, differentiated data services that help our customers make better business decisions, identify risks and opportunities, or become more competitive.”