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TechCapital Group

Established in 1992, TechCapital Group is a private global investment firm that originates, structures and acts as lead equity investor in equity private placements. The R&D management consulting unit provides decision support tools to advanced scientific based engineering groups.

REAL-TIME DISCOVERY BENEFITS

TechCapital’s discovery solution helps advanced R&D engineering groups:

  • Fuel product pipelines with new products and product refinements.
     
  • Decrease information discovery and research time by 40%.
     
  • Maximize revenue by enhancing the ability to make smarter, faster R&D product decisions.
     
  • Identify changes in emerging technologies on a global bases.
     
  • Prioritize, rank and filter derivative technology players and opportunities to jump start market entry.
     
  • Deliver unprecedented efficiency to the innovation effort.


 

 
The Need

Challenges of R&D Decision Support Frameworks

Advanced R&D groups today are typically challenged by:
  • Constrained engineering resources: To continually and systematically assess threats, emerging changes and opportunities to the global technology landscape appropriate engineering resources are typically constrained.
     
  • Overloaded with information from multiple disparate resources: In most cases, business decision-makers do not want a large collection of data. They want data to be compiled and analyzed, with different scenarios and their corresponding advantages and challenges laid out so the decision-makers can draw rapid conclusions and act on them. In many conditions R&D executives are overloaded with unstructured data, this data has a need to be further sorted, classified and analyzed.
     
  • Ad hoc methods: The Technical Intelligence support function in most conditions is not an established ongoing discipline and could be strengthened within R&D. Assessment of R&D partnering opportunities could be identified in a more timely, accurate, disciplined and rigorous manner.
     
  • Lack of skill sets: Due to the difficulty of blending scientific inquiry, artificial intelligence/data mining, IP and R&D decision support resources, the ability to deploy a meaningful TI program is somewhat challenging.
     

 

 

   
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