Building Shiksha: My 10-Day Voice Agent Journey with Murf Falcon

For the last 10 days, I have been building a voice agent called Shiksha as part of the 10 Days of Voice Agents — VoiceForBharat Edition challenge by Murf AI. My original idea was simple: Build a voice agent that can help students learn through natural conversation. Over the challenge, that idea grew into a complete voice-based learning system with memory, tools, human escalation, call analytics, and a specialist agent . What is Shiksha? Shiksha is a voice-based learning partner for students. Instead of typing questions and reading answers, a student can simply talk to Shiksha. A student can: Ask learning questions Take quizzes Continue learning with their saved profile Get help when they are stuck Practice mathematics Get transferred to a Maths Specialist when needed The main goal was to make the experience feel more like a conversation than a traditional chatbot. Tech Stack Component Technology Real-time voice LiveKit Speech-to-Text Deepgram LLM Gemini Text-to-Speech Murf Falcon Backend Python Memory SQLite Call analytics Flask + SQLite External data Open Trivia Database The voice experience is powered by Murf Falcon , which was one of the main parts of the challenge. How Shiksha Works At a high level, the system looks like this: STUDENT │ ▼ LiveKit Real-time Audio │ ▼ Deepgram Speech-to-Text │ ▼ Gemini Agent Reasoning │ ┌────────────┼─────────────┐ │ │ │ ▼ ▼ ▼ Memory Tools Handoff SQLite Quiz API Maths Specialist │ │ │ └────────────┴─────────────┘ │ ▼ Murf Falcon Text-to-Speech │ ▼ STUDENT This was the basic architecture that I built and expanded throughout the challenge. What I Built 1. Student Memory One of the first things I added was a simple memory system using SQLite. Shiksha can store: Student name Current learning level Topics covered Last interaction This means the agent can use information from previous conversations instead of starting from zero every time. 2. Real Tool Calling For quizzes, I didn't want the agent to always generate questions from memor