Ticket Contents

Description

Student drop-off after onboarding is one of the biggest challenges in large-scale government deployments of TAP's learning platform. Contributing factors include limited digital familiarity, lack of parental awareness, inconsistent school follow-up, and low motivation without reminders. This project involves building AI-powered multilingual voice agents that proactively call students and families, guiding them back into their learning journeys in local languages (Hindi, Marathi, Punjabi). Unlike SMS or WhatsApp reminders, voice conversations allow contextual nudging, task explanation, and personalized interaction, making them significantly more effective for re-engagement.

Goals & Mid-Point Milestone

Goals

• Design a scalable voice agent architecture supporting automated outbound calls via phone and WhatsApp
• Implement multilingual interaction with automatic language detection (Hindi, Marathi, Punjabi)
• Build a learning nudging engine integrated with TAP's LMS to personalize calls based on student activity
• Design structured conversational flows with fallback and escalation logic
• Implement an experimentation framework to measure impact on engagement metrics (return-to-learning rate, completion rate, parent engagement)
• [Goals Achieved By Mid-point Milestone]: Working voice agent prototype capable of initiating automated outbound calls in at least one language with a basic conversational nudging flow connected to the LMS

Setup/Installation

No response

Expected Outcome

A working multilingual voice agent prototype
Integration with TAP’s learning management system
Ability to initiate automated calls and handle simple conversations
Language detection and response in supported languages
Documentation for scaling the system in government deployments

Acceptance Criteria

• Multilingual voice agent prototype handles end-to-end spoken conversations
• Integrated with TAP's LMS for learner context and progress updates
• Automated outbound calling with inbound conversation handling
• Language detection routes responses in supported languages
• Documentation covers scaling and government deployment operations

Implementation Details

• Voice agent framework: VAPI or similar voice orchestration platform
• Calling channels: standard telephony APIs + WhatsApp calling/voice integration
• Multilingual STT/TTS pipelines for Hindi, Marathi, and Punjabi
• LMS integration via TAP's Frappe backend REST APIs to retrieve student activity and progression data
• Conversational flow design: structured dialogues, fallback logic, escalation paths
• Experimentation infrastructure for measuring and logging engagement impact metrics

Mockups/Wireframes

No response

Product Name

Multilingual Voice Agent for Student Engagement and Learning Nudges

Organisation Name

The Apprentice Project

Domain

⁠Education

Tech Skills Needed

Artificial Intelligence, Natural Language Processing, WebSockets, RESTful APIs

Mentor(s)

TBD

Category

AI