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Inpact - AI-Powered Creator Collaboration & Sponsorship Matchmaking

Inpact is an open-source AI-powered platform designed to connect content creators, brands, and agencies through data-driven insights. By leveraging Generative AI (GenAI), audience analytics, and engagement metrics, Inpact ensures highly relevant sponsorship opportunities for creators while maximizing ROI for brands investing in influencer marketing.

Features

AI-Driven Sponsorship Matchmaking

  • Automatically connects creators with brands based on audience demographics, engagement rates, and content style.

AI-Powered Creator Collaboration Hub

  • Facilitates partnerships between creators with complementary audiences and content niches.

AI-Based Pricing & Deal Optimization

  • Provides fair sponsorship pricing recommendations based on engagement, market trends, and historical data.

AI-Powered Negotiation & Contract Assistant

  • Assists in structuring deals, generating contracts, and optimizing terms using AI insights.

Performance Analytics & ROI Tracking

  • Enables brands and creators to track sponsorship performance, audience engagement, and campaign success.

Tech Stack

  • Frontend: ReactJS
  • Backend: FastAPI
  • Database: Supabase
  • AI Integration: GenAI for audience analysis and sponsorship recommendations

Workflow

1. User Registration & Profile Setup

  • Creators, brands, and agencies sign up and set up their profiles.
  • AI gathers audience insights and engagement data.

2. AI-Powered Sponsorship Matchmaking

  • The platform suggests brands and sponsorship deals based on audience metrics.
  • Creators can apply for sponsorships or receive brand invitations.

3. Collaboration Hub

  • Creators can find and connect with others for joint campaigns.
  • AI recommends potential collaborations based on niche and audience overlap.

4. AI-Based Pricing & Contract Optimization

  • AI provides fair pricing recommendations for sponsorships.
  • Auto-generates contract templates with optimized terms.

5. Campaign Execution & Tracking

  • Creators execute sponsorship campaigns.
  • Brands track campaign performance through engagement and ROI metrics.

6. Performance Analysis & Continuous Optimization

  • AI analyzes campaign success and suggests improvements for future deals.
  • Brands and creators receive insights for optimizing future sponsorships.

Getting Started

Prerequisites

Ensure you have the following installed:

  • Node.js & npm
  • Python & FastAPI
  • Supabase account

Installation

1. Clone the repository

 git clone https://github.com/your-repo/inpact.git
 cd inpact

2. Install Frontend Dependencies

cd client
npm install

3. Install Backend Dependencies

cd server
pip install -r requirements.txt

4. Set Up Environment Variables

Create a .env file in both the frontend and backend directories with necessary API keys and Supabase credentials.

5. Start Development Servers

  • Frontend:
npm start
  • Backend:
uvicorn main:app --reload

Contributing

We welcome contributions from the community! To contribute:

  1. Fork the repository.
  2. Create a new branch for your feature (git checkout -b feature-name).
  3. Commit your changes (git commit -m "Added feature").
  4. Push to your branch (git push origin feature-name).
  5. Open a Pull Request.

Overall Workflow

graph TD;
  A[User Signup/Login] -->|via Supabase Auth| B[User Dashboard];
  
  B -->|Fetch Audience & Engagement Data| C[AI-Powered Sponsorship Matchmaking];
  C -->|Suggest Ideal Brand Deals| D[Creator Applies for Sponsorship];
  D -->|Submit Application| E[Brand Reviews & Shortlists];
  E -->|AI-Based Pricing & Negotiation| F[Contract Generation via AI];
  F -->|Sign Deal| G[Sponsorship Execution];
  
  G -->|Track Performance| H[AI-Powered ROI Analytics];
  H -->|Optimized Insights| I[Brands & Creators Adjust Strategies];
  
  I -->|Feedback Loop| C;
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FRONTEND workflow in detail

graph TD;
  A[User Visits Inpact] -->|Supabase Auth| B[Login/Signup];
  B -->|Fetch User Profile| C[Dashboard Loaded];

  C -->|Request AI-Powered Matches| D[Fetch Sponsorship Deals via API];
  D -->|Display Relevant Matches| E[User Applies for Sponsorship];

  E -->|Send Application via API| F[Wait for Brand Response];
  F -->|Fetch Application Status| G[Show Application Updates];

  G -->|If Approved| H[Contract Generation Page];
  H -->|AI Drafts Contract| I[User Reviews & Signs Contract];

  I -->|Start Campaign Execution| J[Track Sponsorship Performance];
  J -->|Show Performance Analytics| K[AI Optimizes Future Matches];
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BACKEND workflow in detail

graph TD;
  A[User Authentication] -->|Supabase Auth API| B[Verify User];
  B -->|Store User Data in DB| C[Return JWT Token];

  C -->|Fetch User Profile| D[Return Profile Data];

  D -->|Receive Sponsorship Match Request| E[Query AI Engine];
  E -->|Analyze Audience & Engagement| F[Generate Sponsorship Matches];
  F -->|Return Matches via API| G[Send to Frontend];

  G -->|User Applies for Sponsorship| H[Store Application in DB];
  H -->|Notify Brand| I[Brand Reviews Application];

  I -->|Brand Approves/Rejects| J[Update Application Status];
  J -->|If Approved| K[Generate AI-Powered Contract];

  K -->|AI Suggests Pricing & Terms| L[Store Finalized Contract in DB];

  L -->|Track Campaign Performance| M[Analyze Engagement & ROI];
  M -->|Return Insights| N[AI Refines Future Recommendations];
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Contact

For queries, issues, or feature requests, please raise an issue or reach out on discord server.

Happy Coding!