Inspiration

Education system faces chronic challenges:

  • Lack of Teaching Assistants (TA) and resource imbalance between teachers and students
  • Inconsistent feedback and assessment quality
  • Limited access to personalized tutoring and learning analytics

What it does

  • Teachers to automate test creation, grading, and feedback
  • Students to receive personalized AI guidance, adaptive feedback, and multimodal interaction
  • Schools to monitor analytics and optimize resource use

How we built it

  • Frontend (Next.js): Modern React-based UI with responsive dashboards for teachers and students
  • Backend (Next.js API Routes): Handles test generation, student submissions, AI requests, and feedback pipelines
  • AI Core (Wrapper Layer): GPT-4.1 nano powered reasoning engine with custom middleware for routing and refinement
  • Voice Layer: Integrated speech recognition (input) and text-to-speech synthesis (output) for natural interaction
  • Database (MongoDB): Stores user data, test responses, AI-generated feedback, and analytics
  • Deployment: Cloud-native via Vercel, scalable and secure
  • Analytics Dashboard: Lightweight metric cards display submission rates, feedback completion, and engagement trends

Challenges we ran into

  • Grok's model were not able to handle web search to suggest relevant resources

Accomplishments that we're proud of

  • Edaptix is a revolutionary idea, as edutech systems with automated summaries and feedback rarely exist. Even when they exist, they are quite general.
  • We fixed the issue for relevant resources by deploying tavily's search agent and integrated that with Grok's Llama model.

What we learned

  • One model/AI is often not enough/robust
  • Building an AI workflow

What's next for Edaptix

  • Plagiarism reports for students and teachers
  • Ability to handle image data
  • RAG for problems and syllabus bank

Built With

  • gpt
  • langchain
  • nextjs
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