RepReady
Practice the hardest sales conversations before they happen live.
RepReady is an AI-powered B2B sales negotiation simulator that helps sales professionals master objection handling and negotiation tactics in a zero-risk environment.
Features
🎯 AI-Powered Personas
- Richard (VP Procurement) - 5-star difficulty, aggressive negotiator with 20 years of experience
- Sandra (IT Director) - 4-star difficulty, polite but always has blockers
📊 Real-Time Scoring
- Dynamic Deal Health Score (0-100) that evaluates YOUR negotiation tactics
- Score drops for bad behaviors (offering discounts early, apologizing for price)
- Score rises for good behaviors (discovery questions, holding firm on price)
- Instant feedback explaining what you did right or wrong
📝 Performance Scorecards
- AI-generated performance reviews after each session
- Strengths and areas for improvement
- Key learning moments highlighted
🏢 Enterprise Features
- Email-gated access with 3 free sessions
- Session history tracking
- Team access request system
- Privacy-compliant with GDPR, CCPA, and DPDP Act 2023
Tech Stack
- Frontend: Next.js 14 (App Router), React, Tailwind CSS, shadcn/ui
- Backend: Next.js API Routes with streaming responses
- AI: Google Gemini 2.5 Flash via Vercel AI SDK
- Database: MongoDB
- Styling: Glass-morphism design, dark enterprise theme
Getting Started
Prerequisites
- Node.js 18+
- MongoDB instance
- Google Gemini API key
Installation
- Clone the repository:
git clone https://github.com/V619-maker/repready.git
cd repready
- Install dependencies:
yarn install
- Create a
.env file:
MONGO_URL=mongodb://localhost:27017
DB_NAME=repready
GOOGLE_GENERATIVE_AI_API_KEY=your_gemini_api_key
NEXT_PUBLIC_BASE_URL=http://localhost:3000
CORS_ORIGINS=*
- Run the development server:
yarn dev
- Open http://localhost:3000 in your browser.
API Endpoints
| Endpoint | Method | Description |
|---|
/api/negotiate | POST | Stream AI negotiation responses |
/api/scorecard | POST | Generate performance scorecard |
/api/register | POST | Register user email |
/api/user | GET | Get user data |
/api/user/session | POST | Increment session count |
/api/sessions | GET/POST | Manage session history |
/api/request-access | POST | Request team access |
Scoring Logic
The AI evaluates the sales rep's behavior, not the persona's responses:
Score Drops (Bad Behavior)
- Offering discount before establishing value → 15-25
- Apologizing for price → 20-30
- Offering free implementation unprompted → -20 points
- Immediately agreeing to demands → -15 points
Score Rises (Good Behavior)
- Asking discovery questions before pitching → 65-75
- Holding firm on price when challenged → 70-80
- Reframing conversation to value/ROI → +15 points
- Professional pushback on demands → +10 points
License
MIT License - see LICENSE file for details.
Contact
For support or inquiries: [email protected]
