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VoxMate

VoxMate — A Voice-First AI Companion VoxMate is a real-time multimodal AI companion designed to bridge the gap between simply asking an AI something and having an AI that can actually understand, assist, and act. The system combines real-time conversational voice AI, multilingual interaction, intelligent tool use, and visual understanding into a single experience. Users can speak naturally in English, Hindi, or Hinglish, without needing to formulate perfectly structured commands. VoxMate understands the user's intent and can respond conversationally while interacting with the digital environment when required. What makes VoxMate different? Instead of treating AI as a text chatbot, VoxMate is designed as an action-oriented conversational assistant. Behind a simple voice conversation, the system can intelligently determine whether the user needs information, assistance with a digital task, navigation, communication, or visual understanding — and then use the appropriate capability. The goal is simple: Talk naturally. Let the AI understand the intent. Let it handle the next step. Core Experiences 🎙️ Calling Buddy — Real-Time Voice Assistance A multilingual voice companion powered by Agora Conversational AI. It supports natural, two-way voice conversations and is designed to handle real-world requests rather than just answering questions. The experience combines speech recognition, conversational intelligence, voice synthesis, and external capabilities to turn spoken requests into useful actions. 👁️ Visual Assistance VoxMate can also understand the visual world around the user. Through camera-based and image-based interaction, users can provide visual information and ask the AI to interpret what it sees. The visual experience includes capabilities such as: Live visual understanding Image-based AI analysis Text recognition Interactive visual questions A specialized assistance mode for health-related visual guidance Spoken AI responses for a more accessible experience The interface is designed around a simple idea: show the AI what you see, then ask what you want to know. 🤟 Accessibility-Oriented Assistance The project also explores ways conversational AI can make communication more accessible through visual and sign-based interaction, extending the assistant beyond conventional voice-only interfaces.

Evident

Evident — an AI interview panel that proves its feedback. Interview practice today is a chatbot and an arbitrary number. Evident is a live voice panel: two AI interviewers with genuinely different jobs — Priya grades technical depth and trade-offs, Sam challenges customer impact and clarity. They listen to what you actually say, take the floor from each other by rule, interrupt and get interrupted gracefully, quote your own earlier claims back at you when you contradict yourself, and adapt difficulty to how you're doing. The whole interview runs in English, Hindi, or Hinglish. The architecture is the point: an LLM only labels each answer — pure, unit-tested code decides who speaks next, why, and when the interview ends. Scores are a deterministic function of an evidence ledger, and every quote in the report is verified verbatim against the transcript — feedback that cannot be hallucinated, ending only when all four competencies have real evidence, never on a timer. Then it closes the loop: your weakest skill with the exact answer that cost you, a written lesson, a targeted quiz, and a focused re-interview — with a progress page that proves the score moved. One Agora agent, per-turn voice switching, a single OpenAI-compatible endpoint as the panel's brain, and an offline test suite that runs the entire Director with every vendor down.

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