HackathonFeatured ProjectStatus: Award Winner38 Stars

Sahayog

Voice-first AI assistant concept designed to break digital literacy barriers for regional users.

Sahayog
My RoleHackathon Lead & Conversational AI Developer
Timeline / Duration36 Hours (Hackathon Sprint) + 2 Weeks Polish
Team Structure4 Members
THE CORE PROBLEM

Millions of elderly and regional language speakers in rural areas find complex form-based smartphone interfaces intimidating and inaccessible.

THE ENGINEERED SOLUTION

Sahayog provides a zero-touch, conversational voice interface that converts speech into structured actions (such as checking crop prices, setting reminders, or filing service queries) in conversational Hindi and Marathi.

PRODUCT CAPABILITIES

Key Features & Engineering Highlights

Continuous speech-to-text with auto noise cancellation for ambient outdoor use
Context-aware intent classification translating conversational speech into API payloads
Audio feedback synthesizing natural human-like responses in regional languages
Offline capability for critical emergency contact speed-dial commands

Technology Stack

ReactWeb Speech APIPythonFastAPIGemini AI APITailwind CSS
SYSTEM DESIGN

Technical Architecture

Microphone input is captured on the browser via Web Speech API, sent to a FastAPI inference engine that extracts intent with an LLM, and dispatches downstream microservices.

Voice Input / Output

Real-time audio visualization waveform and instant transcript feedback.

Web Speech RecognitionWeb Audio APIReact UI
Conversational Brain

Extracts user intent and required parameters (e.g. city, commodity, action).

FastAPIGemini AI APILangChain Intent Parser
Service Connectors

Fetches real-time commodity rates and public advisories.

Government Open Data APIsWeather APIsMarket Mandi APIs
DEEP DIVE CHALLENGES

Technical Obstacles & Solutions

Handling Accented Regional Indian English and Dialects

Problem Encountered:

Standard ASR models frequently misunderstood regional terminology.

Engineered Resolution:

Implemented an acoustic phonetic mapping layer that corrects colloquial phrasing before feeding to the LLM.

Measurable Results & Impact

Recognized at regional hackathon for social impact and human-centric design

88% task completion rate among first-time non-English speaking testers