Artificial Intelligence is a branch of
Science which deals with helping machines find
solutions to complex problems in a more human-like
fashion. This generally involves borrowing characteristics
from human intelligence, and applying them as
algorithms in a computer friendly way. A more
or less flexible or efficient approach can be
taken depending on the requirements established,
which influences how artificial the intelligent
Our core emphasis is on Research and Development.
Mustus is evolving into India's most advanced
R & D organization, with state-of-the-art
design and development environments. Our team
of highly qualified professionals works on R &
D tracks covering expert systems in Agriculture,
Medical and Financial domain and diversified range
of products in Natural Language Processing.
Some of the projects under this section are:
A different approach that brings the power of
NLP in liaison with the Financial Expert Systems
to bring out the Normalization in the data extraction
process, thus lead to reliable and convenient
way to address the retrieval process.
Dhanvantari is a cross-lingual medical information
system that simulates real-life human dependent
medical system using NLP based query understanding
and intelligent information retrieval in different
linguistic domains.The crux of the system lies
in grasping user queries in any natural language
form and resolves them using semantic-pragmatic
sense-retrieval in different modes of information
A Natural Language Processing based Packet sniffer
that analyzes, simulates and monitors each passing
packets to identify the sensitive ones depending
upon the rules and logs them for future references.
A English-Hindi sense translator that takes out
the meaning of the text and translates it in hindi
language thus enabling the user to understand
the meaning of the text. The system is designed
as a part of the pilot project for the concept.
The team is taking the concept across german,
spanish and french languages..
A project designed to enable the quantitative
comparison of different approaches to automated
word-sense disambiguation, in English and other
languages. In order to prepare the data used in
the evaluation, sense-tagging tools are being
developed. This exercise also provides an opportunity
to assess the validity of our lexicon's sense
inventory and to associate English word senses
with those from the other evaluation languages.