PLATAFORMA VIRTUAL DE MATURIDADE TECNOLÓGICA

Abstract

Technological Readiness Levels (TRL’s) are widely used as eligibility criteria in innovation funding calls; however, many organizations—particularly micro and small enterprises—face difficulties in accurately identifying the development stage of their technologies. The absence of accessible, standardized, and reliable instruments for measuring technological maturity undermines the alignment of proposals with funding agencies’ requirements and may limit access to innovation resources. This study proposes and develops a Virtual Technological Maturity Platform, grounded in technological auditing and structured around TRL levels, capable of diagnosing the development stage of technologies, supporting decision-making, and guiding qualified submissions to funding mechanisms. The research is based on a theoretical review of technological auditing, innovation management, and TRL, as well as on the analysis of consolidated technology assessment models employed by renowned institutions. From this framework, a diagnostic instrument composed of parameterized strategic questions was developed and subsequently implemented in a web-based digital platform. As a Technical Technological Product, a digital solution was conceived to automatically identify the TRL of projects, organizations, or solutions, systematizing strategic information and providing guidance regarding compliance with funding calls and programs. The platform contributes to strengthening innovation governance and bridging science, technology, and the market. The adoption of a structured TRL-based technological auditing instrument can enhance organizations’ capacity to understand their technological positioning, improve R&D&I proposals, and increase the likelihood of securing funding. The Virtual Technological Maturity Platform demonstrates potential to strengthen the effectiveness of public innovation policies and evidence-based decision-making. Validation will be conducted across different sectors and organizational sizes, with future developments including integration with funding agencies’ databases, incorporation of new metrics, and continuous improvement through analytical intelligence and learning from real-world use.