Project Info

Echo Rep

Inspiration

The idea for Echo Rep came from all of us experiencing those awkward, uncomfortable customer interactions where we didn’t know what to say or do. Those situations we never expected and weren’t trained to handle. We realized that many people face these moments in real life without any preparation. That’s why we built this app: to make training for tough conversations accessible, realistic, and fun by turning it into a game.

What it does

Echo Rep is an AI-powered call center training simulator that helps customer service representatives practice handling real-world conversations with challenging callers. Using voice interaction, it creates realistic scenarios where users must respond to different customer moods, ranging from confused to angry.

How we built it

We built Echo Rep using Gemini AI, which powers the entire caller simulation. Gemini generates dynamic, emotionally realistic responses across different difficulty levels, ranging from a confused customer to a full-blown angry customer.

Challenges we ran into

Finding the right conversation length was tough. Allowing more than 5 messages made calls feel too long and overwhelming, so we had to carefully limit interactions to keep training focused and engaging. We faced some technical issues with voice connection and initialization, where the AI voice sometimes failed to start or sync properly, which affected the flow and immersion of the training. Lastly, when displaying the feedback, the page rendered as raw code rather than clean text, which made it hard to present the results to the user clearly.

Accomplishments we're proud of

As first-time hackathon participants, we’re proud of what we built with Echo Rep. We created a realistic, AI-powered training tool that keeps conversations short and engaging while giving instant feedback. This gamified approach makes learning customer service skills fun and effective.

What we learned

We learned that focused sessions boost engagement and that designing AI to assess tone is challenging but crucial. Gamification really helps turn tough training into a positive experience.

What's next

Next, we plan to add more customer types, improve voice reliability, and build tracking features to make Echo Rep even more impactful. For us, this project is a meaningful step toward helping people feel confident handling real customer calls.

Run and deploy your AI Studio app

This contains everything you need to run your app locally.

Run Locally

Prerequisites: Node.js

Install dependencies: npm install
Set the GEMINI_API_KEY in .env.local to your Gemini API key
Run the app: npm run dev

Analysis

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Metric

Kevin Wang
5
Vianeycodes
1

Figures cover GitHub contributors during the hackathon window. A co-authored commit counts in full for each author, so per-member totals add up to more than the whole-team figures.

Technology

Found in codeClaimed only

HTMLIn code
ReactIn code
TypeScriptIn code
Google GeminiClaimed

3 of 4 appear in the indexed code. 1 claimed on Devpost could not be matched to code, which may simply mean the tool leaves no trace in the repository.

AI coding agents

No AI coding agent signals were found in this repository.

Detected from committed agent config files and commit authorship. Absence of a signal is not proof an agent was unused.

Codebase size

Source size

60 KB

Source files

Counts recognized source files only; vendored directories, binaries and lockfiles are excluded, so this is smaller than the repository on disk.