Findest's innovative scouting service leverages AI and human intelligence to identify advanced technologies for detecting, repelling, and neutralizing crawling insects. This service provides comprehensive, efficient solutions across all technology readiness levels.
Findest offers a cutting-edge scouting service that combines artificial intelligence with human expertise to identify the most effective technologies for managing crawling insects. By leveraging the IGOR^AI platform and TRIZ methodology, we provide a comprehensive overview of potential solutions to detect, repel, and neutralize insects more effectively than traditional research methods. This service is designed to save time and provide a complete technological overview, aiding R&D-driven organizations in their pest control efforts.
Key features:
The service is capable of identifying technologies across the full spectrum of readiness levels, from TRL1 to TRL9. Findest's scouting service has been validated in collaboration with major multinational organizations, ensuring its effectiveness and reliability.
Findest helps R&D teams “find the way” to better outcomes by scaling technology scouting and solution evaluation. It combines scientifically trained scouts with AI platform IGOR^AI, which searches by function across hundreds of industries to identify technologies that perform the needed function regardless of their names or origin. The company also offers “The Universe,” described as a software environment that structures scouting work and supports collaboration and knowledge sharing.
According to Findest, it uses a controlled sequence in The Universe—searching, ranking, document checks, and a “Judge Model” that evaluates accuracy and refines its search multiple times in seconds—while keeping results traceable to their sources. Findest positions its approach as built from hard-won methodology refined through 3,000+ projects and used by R&D teams at 400+ companies, aiming to reduce time spent on research and enable teams to map a complete solution landscape before committing resources.