Abeyon recently contributed to the ACT-IAC white paper on Artificial Intelligence Machine Learning Primer.
About Mallesh Murugesan
Mallesh Murugesan, Founder and CEO of Abeyon, is an innovative leader with 20+ years of experience in Technology and Design. He has been working with the Navy for 15 years in executing strategic IT initiatives, and providing innovative technology solutions. His latest being Artificial Intelligence based text analysis tool that recently won the Government Innovation Award.
Under his leadership, Abeyon has been working on several advanced AI technologies including Text Analysis, Category Management, NLP and more. His latest creation, chirrp.ai is a multi-channel chatbot platform that is powered by cognitive technology. And he has a patent pending on his intent identification methodology in a cognitive conversation.
Mallesh has a Masters in Information Systems from George Mason and an MBA from University of Maryland, College Park
Entries by Mallesh Murugesan
Abeyon contributed to the ACT-IAC white paper on Intelligent Automation Primer. The goal of this primer is to help readers understand how they can adopt various automation technologies to make their businesses more effective. The term Intelligent automation marries artificial intelligence—including natural language processing, machine learning, and machine vision—with automation to replicate and/or imitate human […]
Abeyon, llc (under prime Emprise Corporation) was awarded a spot on SeaPort Next Generation Contract (a a potential 10-year, $50B contract vehicle). Learn More
Abeyon’s work in Artificial Intelligence NLP technology was recognized as the 2018 Government Innovations Award winner among DoD projects for implementing the “Best in Class” machine learning tool Learn More
Microservice is a software development technique for developing an application as a suite of small, independently deployable services built around specific business capabilities. Microservices is the idea of breaking down big, monolithic application into a collection of smaller, independent applications. Why should machine learning models be deployed as microservices? This is an empirical era for […]
As a follow up to my earlier LinkedIn Post of Google’s BERT model on NLP, I am writing this to explain further about BERT and the results of our experiment. In a recent blog post, Google announced they have open-sourced BERT, their state-of-the-art training technique for natural language processing (NLP) applications. The paper released (https://arxiv.org/abs/1810.04805) along […]
Deep Learning is a subset of machine learning that allows machines to do tasks that typically require human like intelligence. The inspiration for deep learning comes from neuroscience, if you look at the architecture of Deep Learning Neural Networks, they are connected in a fundamental way that mirrors the brain. Deep-learning networks are distinguished from […]
A good definition by TechEmergence states that “machine learning is the science of getting computers to learn and act like humans do, and improve their learning over time in autonomous fashion, by feeding them data and information in the form of observations and real-world interactions.” From the definition it is fairly apparent that all forms […]
Chirrp has been featured in the Miami Herald! Writer Nancy Dalberg speaks to chirrp’s leadership about chirrp’s unique technology as part of the Herald’s Biz Monday feature. Check out the full story here or read the transcript below. Chatting with Chirrp: Miami company uses AI to engage with customers By: Nancy Dahlberg, January 12, 2018, 02:49 […]
Chatbots are transforming customer experience! Chirrp is partnering with Accelirate to offer cutting-edge enterprise chatbots solutions. Chirrp enables companies to transform their customer experience by providing human-like conversation. With this partnership, chirrp expands its capabilities by integrating business process automation (BPA) software. To address increasing customer demand for chatbot solutions, Accelirate is looking to chirrp to provide relevant and accurate […]