LAIC - LIVE AI INTERVIEW COACH

MAKE YOUR INTERVIEW SMOOTH

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Inspiration

Technical interviews are one of the most stressful parts of a developer’s career. Many candidates prepare by reading questions or practicing with static tools, but real interviews are dynamic, conversational, and often interrupt-driven. Existing preparation tools mostly rely on text-based chatbots that cannot simulate the real pressure of a live interview.

We wanted to build an AI system that goes beyond text and truly replicates a human-like interview experience — one that can listen, see, speak, and respond in real time. The goal was to create an AI interviewer that behaves like a real human interviewer: asking follow-up questions, interrupting when necessary, and evaluating communication confidence.

That idea became LAIC – Live AI Interview Coach, a multimodal AI agent powered by Gemini Live API.

What it does

LAIC (Live AI Interview Coach) is a real-time multimodal AI interviewer that helps users practice technical interviews through natural conversation.

Unlike traditional chatbots, LAIC creates a live interview environment by combining voice interaction, camera analysis, and AI reasoning.

Key capabilities include:

• Real-time AI interviewer – The AI asks technical and behavioral interview questions through voice. • Natural conversation flow – Users can respond verbally and the AI can interrupt or ask follow-up questions naturally. • Vision-based feedback – Using camera input, the system analyzes posture, engagement, and eye contact. • Confidence analytics – LAIC generates a live confidence score based on speech clarity, tone, and engagement. • Technical evaluation – The AI analyzes answers and provides feedback on explanation quality and technical depth. • Interview performance report – After the session, users receive an analytics dashboard showing strengths and areas for improvement.

The result is a fully immersive interview practice environment that feels much closer to a real interview than traditional AI chat tools.

How we built it

LAIC is built as a monolithic full-stack application using Next.js, allowing both frontend and backend logic to live in a single architecture.

Frontend

The frontend provides the interactive interview experience.

Technologies used:

  • Next.js
  • React
  • TailwindCSS
  • WebRTC for real-time audio and video capture
  • Web Speech APIs for audio processing

The UI includes:

  • live camera feed
  • audio waveform visualization
  • real-time interview transcript
  • confidence score dashboard

AI Layer

The AI layer is powered by Gemini Live API, enabling:

  • real-time voice conversation
  • multimodal input processing (audio + image frames)
  • interruptible conversation flow
  • contextual reasoning for interview questions

Backend

The backend runs inside Next.js API routes and handles:

  • AI session orchestration
  • audio and vision data processing
  • interview context management
  • analytics generation

Cloud Infrastructure

The application backend is deployed on Google Cloud, leveraging:

  • Cloud Run for scalable backend deployment
  • Vertex AI for Gemini model access
  • Firestore for session data storage
  • Cloud Storage for media assets

This architecture ensures the system is scalable, reproducible, and cloud-native.

Challenges we ran into

Building a real-time multimodal AI agent introduced several technical challenges.

1. Real-time latency

Maintaining smooth voice interaction required minimizing latency between user speech and AI responses. Streaming audio processing and optimizing API calls were critical.

2. Interruptible conversation

Unlike standard chatbots, real interviews involve interruptions and dynamic questioning. Designing the agent to respond naturally required careful prompt engineering and session context management.

3. Multimodal synchronization

Processing voice input, camera frames, and AI responses simultaneously required a coordinated pipeline between the browser, backend services, and AI models.

4. Realistic interview behavior

A key challenge was making the AI behave like a real interviewer rather than a simple question generator. This required designing conversation logic that adapts based on the user's responses.

Accomplishments that we're proud of

We are especially proud of several aspects of LAIC:

• Creating a fully interactive voice-based AI interviewer instead of a traditional chatbot • Successfully integrating multimodal AI interaction (audio + vision) • Building a real-time analytics dashboard that measures interview confidence • Deploying the full system on Google Cloud infrastructure • Demonstrating a complete working prototype within a short hackathon timeframe

Most importantly, we built an experience that feels like a real interview conversation, which is rarely achieved in AI interview tools today.

What we learned

Through building LAIC, we gained valuable insights into the future of AI agents.

We learned that multimodal AI dramatically changes how users interact with intelligent systems. When an AI can hear, see, and respond naturally, the interaction feels significantly more human.

We also learned the importance of latency optimization and streaming pipelines when building real-time AI experiences. Small delays can greatly affect user perception of responsiveness.

Finally, this project reinforced how powerful cloud-native AI platforms like Google Cloud and Gemini models are for building advanced AI applications quickly.

What's next for LAIC – Live AI Interview Coach

While the current version demonstrates the core concept, we see several exciting future directions.

Personalized interview preparation

The AI could analyze a user's resume and tailor interview questions to their background and target companies.

Company-specific interview simulations

Users could practice interviews for companies like FAANG by simulating real interview styles and difficulty levels.

AI coding whiteboard

Integrating a collaborative coding environment where the AI evaluates live coding solutions.

Emotional intelligence analysis

Using advanced vision models to analyze stress signals and provide communication coaching.

Enterprise recruiting tools

LAIC could evolve into a platform used by companies to conduct preliminary AI-powered interviews.

Our vision is to turn LAIC into a next-generation AI interview preparation platform that truly replicates the dynamics of real interviews.

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