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This project aims to create a low-cost, AI-powered dashboard that synthesizes students' academic performance

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Llama Impact Pan-LATAM Hackathon

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EduTrack AI


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This project aims to create a low-cost, AI-powered dashboard that synthesizes students' academic performance, school records, and teacher feedback to improve monitoring, early diagnosis, and communication between schools, families, and professionals.

By Llobo Squad


General Description

  • Project Objective: Create an innovative low-cost informative dashboard assisted by multi-agent AI, which presents the synthesis, insights and projections of the student's school life, taking into account school life records, the student's academic performance and teachers' comments.

  • Justification: The school system's documentation is bureaucratic, making it difficult to monitor students' development and identify cognitive problems early. Students' low level of individual information makes it difficult to prevent and treat signs of problems in the school environment. We are looking for a more robust and efficient solution, using a Multi-Agent system based on Llama 3.1, inspired on the context of the Brazilian educational system, aiming to optimize communication between the school, the family and health and education professionals who require the information for diagnostic assessments, distributing relevant and updated information.

  • Target audience for this project: Users of the education system, education system employees and healthcare professionals who carry out some type of monitoring with students.

Feature Specification

✅ Easy-to-interpret dashboard, partially generated by Llama 3.1 multi-agent system, interpreting the records of academic performance and a brief description of topics of interest to psycho-pedagogy;

✅ Ability to guide, with AI, healthcare and education professionals on how to deal with each occasion through scientific studies;

✅ Point out possible cognitive-behavioral or learning disorders, using the data presented and interpreted by AI, generating an alert to be carried out by more adequate professionals.

What was done during the Llama Impact Pan-LATAM Hackathon:

  • Functional Dashboard in PowerBI based on a Multi-Agent System that uses Llama 3.1 8B Instruct through the SambaNova API;

  • Python Script to Update Excel Base Automatically.

What we plan for the future:

  • Replacing the Excel Base and PowerBI, respectively, with a Relational Database and a Solution for Open Source Dashboards;

  • Support Parent Feedback;

  • Using a Trained Model to Raise More Assertive Diagnostic Hypotheses.

Market Size

Market Overview in Brazil

Approximately 33.8 million students are enrolled in elementary and high schools in Brazil, as per the 2023 School Census. These students are spread across 178,500 schools, with 59.8% in the public network and 23.3% in the private sector.

Target Focus and Goals

The focus is on serving both the public education sector (through government tenders) and the private sector, with an emphasis on efficient, data-driven educational management. The goal is to impact 5% of schools in Brazil, which amounts to about 8,925 institutions, improving the quality of education and school management.

Business Model and Market Potential

The model involves a annual fee of $50 per student, alongside implementation costs for new institutions. The Serviceable Obtainable Market (SOM) is valued at $92.75M, the Serviceable Addressable Market (SAM) at $151M, and the Total Addressable Market (TAM) at $169M.

Technologies Used:

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How to use this project?

  • In the future, the user will be able to access the application through an online portal that will retrieve the dashboard updated with the outputs of the multi-agent system.

How to find help using the project?

Meet the Project Team

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This project aims to create a low-cost, AI-powered dashboard that synthesizes students' academic performance

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