7 World Trade Center,

10th Floor, 

250 Greenwich Street,

New York, NY, 10007

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© 2019 NLMatics Corp.

Discover Insights from  Unstructured



Search for specific clauses such as exclusions and guarantees in complex contracts and agreements.



Detect compliance violations in employee communications.


Manage Risk

Monitor ever increasing volume of text data to fortify your risk management process.


Navigate Regulatory Requirements

Track regulatory changes and translate  regulatory requirements to business rules.


Discover Marketing Opportunities

Understand customer preference and interests to recommend new products.



Automate repetitive research patterns to expedite knowledge discovery and improve productivity.


Org Intelligence

Discover organizational bottlenecks from interactions, feedback and support requests.




Our model output is scored and explained intuitively using relevant phrases contributing to the score.


We deploy multiple strategies to improve relevancy. We expect our models to be reliably used for analytics and predictive modeling.


Our models are designed to work right out-of-the box.


We do not expect domain experts to spend time in curating training data or building ontologies.


Our models learn and adapt to new data and usage patterns.



Our Story

We are a team of researchers, technologists and industry experts determined to  help businesses succeed in the era of overabundant text data using advanced  language comprehension models.

We embarked on this journey because we saw a wide gap between current solutions and customer needs. 


We study latest research, conduct our own, and combine ideas from classical NLP, graph theory, bayesian probabilistic inference, bioinformatics, active learning, reinforcement learning and deep learning to create best-of-breed solutions that are enterprise ready.

Our Vision

We believe that when it comes to application of Natural Language Understanding  to business problems, current solutions have barely scratched the surface. 

Our goal is to develop models that comprehend language the same way humans do and are able to organize and store their knowledge for intelligent responses.

We are committed to rapidly integrate latest research into our products and give back to the research community.

Our Technology

Roughly 90% of data generated today is unstructured. From informal notes to complex legal documents, from news headlines to extensive reports - our technology is designed from ground-up to be flexible so that enterprises do not have to spend on a different system for each class of unstructured text. 



Ambika Sukla

Co-Founder and CEO

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Ambika is an accomplished technology executive with over 20 years of experience in leading large scale technology transformation in the financial services sector.

Ambika established Morgan Stanley’s AI Center of Excellence and headed the AI research and advisory team. Prior to Morgan Stanley, Ambika was a Vice President at Goldman Sachs.

Ambika's  background is in signal processing and information theory and he holds a Masters degree in Telecommunication Engineering from NJIT.

Jan Choy

Head of Product and Strategy

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Jan has led Natural Language Processing (NLP) product and commercialization efforts for over a decade across numerous use cases in customer engagement, risk monitoring and operational efficiency.   

After launching IBM Watson in the finance vertical, Jan worked with startups Digital Reasoning and Petuum to deliver multiple large-scaled NLP digital innovations. She has experienced the evolution and adoption of enterprise machine learning and language analytics as more companies invest in unraveling unstructured data.


Jan has an MBA from Columbia Business School and a BA in Computer Science from Wellesley College.  In her early career, she worked on the algorithmic trading desks at JPMorgan and Lehman Brothers.  




Dr. Bülent Yener


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Professor of Computer Science

Rensselaer Polytechnic Institute

Heng Ji

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Professor of Computer Science 

University of Illinois at Urbana-Champaign

Charlie Federman

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