AntWorks: Deriving Meaningful Insights From Unstructured Data

CIO Vendor In today’s age of data explosion,businesses encounter the challenge of extracting value from the burgeoning unstructured data in the enterprise environment. The current goal of every enterprise is to segregate data with similar traits and classify them into clusters to make the best use of it. With the digital wave taking over, Machine Learning is proving to be particularly strong in solving the classification and clustering of data challenges. Machine Learning is being leveraged to make pattern based decisions to automate processes and augment the accuracy of data-driven tasks.

One of the largest Title Insurers in the world set out to look for an intelligent automation provider to achieve its very data intensive goals. This company facilitates and streamlines real estate transactions by providing comprehensive title insurance protection and professional settlement services. One of their processes involved generating a title report after examining close to 49 different types of documents related to a property, in order to evaluate the chain of title sanctity. The daunting challenge was that the documents to be examined were highly unstructured documents - rendered not automatable with traditional OCR. To compound issues, the documents contained poor quality images due to dated records. Experienced examiners had to scrutinize documents using a highly recursive examination process resulting in very high handling times. These examiners had to go through intensive training before they could generate a title report.

After a careful assessment of technologies by the client, AntWorks fulfilled the requirements of the client with its novel platform, ANTstein powered by fractal science. The platform enabled the automation of the process by collecting and analyzing more than 1000 data elements to support improved decision making.Additionally, the solution could be trained to turn data into meaningful insights in either a supervised or adaptive mode.

Enabling informed decision making
The company could leverage the multiple capabilities of AntWorks’ ANTstein stack to read and analyze dozens of unstructured documents, thereby reducing time and effort spent on investigating properties’ title sanctity, thus ensuring correct decision making. “ANTstein TitleBOT is capable of reading, capturing and inferring from structured and unstructured data present in multi formatted title documents such as Deeds, Deed of Trusts, Judgment and Tax documents and so on,” explains Asheesh Mehra, CEO at AntWorks. The TitleBOT integrates adaptive, supervised and reinforcement Machine Learning algorithms to improve accuracy of extraction and decision making. ANTstein platform includes Cognitive Machine Reading (Machine Vision), Natural Language Modeling, and Data Reinforcement algorithms to secure data availability and integrity; while Machine Learning and Deep Learning drive optimal decision making.

Dealing with the adversity of unstructured data
The Cognitive Machine Reading (CMR) engine has been designed and developed as the key to every enterprise’s unstructured data woes. Ahead of its competitors in the market and equipped with the capability to ingest structured, unstructured, semi-structured, inferred and image-based data, the engine ceaselessly works on detecting text and non-text in auto-mode, image reading and recognition, and Cognitive Machine Reading based on patterns. The featurerich engine meets and exceeds the demands of clients with its highly scalable, GUI based interface, non-intrusive configuration and distributed computing that assures robust security. It possesses unique benefits such as seamlessly handling multiple data formats into a single platform, attaining 85 percent data accuracy in the very first attempt with Machine Learning reaching 95 percent accuracy within three to five months of deployment of the solution, something that most vendors aspire to accomplish.
The robustness and power of the integrated data ingestion and digitization permits 90 percent improved productivity and zero errors in processing.


Our proprietary machine learning engine, the only one powered by fractal science makes the adoption of machine learning a lot more efficient. As a science, it lends itself to smaller data sets for high yields of learning and lighter infrastructure for deployments, making machine learning more affordable for businesses and easier and faster to deploy


Deploying Machine Learning Solutions at an Economical Cost
AntWorks addresses all the three automation building blocks which areMachine Vision, RPA and Machine Learning. “Our proprietary Machine Learning engine, the only one powered by fractal science makes the adoption of machine learning a lot more efficient. As a science, it lends itself to smaller data sets for high yields of learning and lighter infrastructure for deployments, making Machine Learning more affordable for businesses and easier and faster to deploy,” adds Asheesh.

Engineered for process design flexibility and empowering business users to create, test and deploy bots to automate processes as well as obviating the need to write even a single line of code, ANTstein minimizes human intervention. A softbot that smartly performs a broad range of actions continuously and autonomously on behalf of the stakeholders, promises an integrated platform with lower total cost of ownership, faster return on investment, centralized digital workforce management, graphic user interface for faster enterprise adoption with built-in digital workforce governance. Apart from offering advanced operational and business analytics, the platform is armed with report extraction with customized format that is available on request.

With better control over the data lifecycle, the combination of a full stack with industry-rich expertise gives the company a strategic vantage point to analyze and solve industry specific problems by building complex industry specific and process specific BOTS such as Tax BOT, Title Search BOT, Trade Finance BOT and Logistics BOT to name a few. These bots are backed by robust vertical knowledge based repositories of processes within that industry. These are POINT BOTS where 80 percent is standardized and 20 percent configured for client specific environments. These BOTs are made available with existing training, maintaining domain knowledge and having the capability to solve specific process automation challenges. The revolutionary BOTS can even read specific industry documents, apply rules, learn, and process. “The availability of the entire stack allows us to look at automation through a different lens than just a stand-alone RPA company. We see automation being far more compelling when combined with deep domain expertise,”says Asheesh.

Continually striving to maintain its leadership position in the market, AntWorks recently infused adaptive, supervised and re-enforcement algorithms in its innovative platform to better serve customers and diligently work towards constantly updating the platform. Believing it has just scratched the surface of what Machine Learning and Artificial Intelligence has to offer, AntWorks envisions a future of vertical specific bots that will further drive business value. Perfectly poised with its end-to-end intelligent platform, the company aims to put AntWorks on the map for every enterprise on the lookout for cutting-edge Machine Learning solutions.