Automated Competitive Intelligence Product for Decision-Making and Training in the Innovation Enterprise
Award last edited on: 7/16/2015

Sponsored Program
Awarding Agency
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Solicitation Topic Code

Principal Investigator
Uma Kaundinya

Company Information

Aavishkar LLC (AKA: Aavishkar Innovations, Inc)

215 Concord Road
Bedford, MA 01730
   (617) 721-5665
Location: Single
Congr. District: 06
County: Middlesex

Phase I

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This Small Business Innovation Research Phase I project proposes to build an automated, smart competitive intelligence product for education, training and decision-making in academic innovation management. Currently, $40b- $60b of tax payer dollars is spent in academic research. Yet, 80% of inventions that arise from this investment in academic research do not impact society as product(s) or revenue. The key deficiencies of current processes include, costly and time-consuming decision-making, and lack of training, education and work-flow. This ultimately has resulted in lack of best practices in academic innovation management. This project would result in products that would educate and cross- train inventors and invention managers, would produce automated and appropriate decisions for every invention and would streamline workflow, thus defining best-practices for the industry. This project would have several positive impacts, including lowering costs and increasing business partnerships for academic inventions. Such increase in business partnerships would increase products and revenue. Thus, as a result of this project, the potential of dormant inventions would be realized, which would in-turn creates jobs and fuel reinvestment into the innovation economy. Thus the product would leverage the billions invested in academic research.

This project proposes to build a product for automated invention management and decision-making. The decision-making is empowered by information or data aggregated from disparate sources in several domains as well as by assimilation of personnel insights. This is accomplished by the design that allows collection of data from several sources in multiple domains and providing the most relevant data to the user in the context of the invention. The mathematical modeling used to develop the decision-making technology is based on objective criteria rather than on subjective criteria. The product resulting from this project will be hosted in the cloud with unique access points to several layers of users. The user-interfaces and the analytical output will be customized to the type of user. Moreover, the design accommodates multiple users at the different layers and will serve as a web-portal for collaboration. The overall goal of the research project is to provide an automated innovation decision-making product that is customizable to suit the risk profiles of different academic innovation centers. The goal of the Phase I project is to build a proof-of-concept product that can undergo testing.

Phase II

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