Readia: AI Capabilities Diagnostic Platform

Purpose and Methodological Framework

• Academic Origin: The Readia project was conceived and developed as a university final degree project. Its primary objective transcended technical implementation, focusing on teaching and the practical application of information technology project management within a controlled yet professional environment.
• Management Standard: To ensure the success of the deliverables, the PMBOK model, 6th edition (Project Management Body of Knowledge) was rigorously adopted. This regulatory framework allowed for structured administration of knowledge areas, including scope, activity scheduling, cost management, and quality control.

The implementation of the PMBOK methodology ensured that Readia’s development maintained a clear trajectory from the charter to project closure. Thanks to this approach, it was possible to mitigate technical risks early on, especially those related to cloud service interoperability, aligning academic goals with high-level software execution.

Diagnostic Process and User Flow

• Business Profile Registration: The user journey begins with the creation of a detailed profile. Through an intuitive form, fundamental data such as the industrial sector, organization size, and strategic vision regarding technology are collected.
• Initial Context Questionnaire: Once the profile is established, the system displays a series of predefined questions. These questions act as a standardized reference frame to place the company within an initial maturity spectrum.
• Dynamic Question Generation: Readia’s innovative core lies in its adaptability. Using the AI engine, the system analyzes previous responses in real-time to formulate new specific questions that delve into detected critical areas.

This iterative flow transforms data collection into an intelligent conversation. By answering these dynamically generated questions, the user provides a much richer and more specific context than a traditional static form would allow.

The interactivity of the form ensures that each diagnostic is unique. This dynamic behavior is essential for the artificial intelligence to possess the necessary depth of field to project a strategic roadmap that is truly applicable to the company’s reality.

Visualization, Customization, and Collaboration

• Diagnostic Report: After processing the information, the platform generates a comprehensive report. This document evaluates the organization’s strategic pillars against the demands of AI adoption, presenting clear metrics and areas for improvement.
• Context Customization: Readia offers post-diagnostic flexibility, allowing users to return and modify the context of their initial responses. This facilitates the simulation of different scenarios or profile updates in response to organizational changes.
• Sharing Functionality: A collaboration system was integrated, allowing users to send previews of the results to other organization members or stakeholders using simply their username or institutional email.

The user interface has been designed to be professional and analytical. The dashboards do not just present data; they tell a story about the company’s current capacity, allowing both technical profiles and decision-makers to understand findings immediately.