Flybridge Investment Memorandum Generator

Overview

The Flybridge memo generator tool helps turn decks, business plans, and call notes into a first-draft VC investment memo for AI startups. For founders, it offers insights into how VCs might evaluate your business and simplifies the process of presenting your company to investors by creating a draft memo based on the information provided. To get the most accurate results, provide as much context as possible. A helpful tip is to record your pitch and upload the transcript along with any supporting materials.

Limitations

The memo generator produces a strong draft addressing key investor considerations but serves as a starting point, not a finished product. It covers 50-60% of the work, requiring human input for nuance and judgment. The tool may reflect biases in the input and is limited by OpenAI's o1 model. Competitor analysis provides initial insights but should be supplemented with additional research, and market size estimates should include a separate bottoms-up analysis. This tool is for informational purposes only.

Features

Smart Document Processing

• Support for multiple document formats (PDF, Word, scanned documents)
• Built-in OCR capability for processing scanned materials
• Web content integration through URL processing

Agentic research analysis

• Automated market research and competitor analysis
• Market size and growth rate calculations

Team Analysis

• LinkedIn profile integration for founder background analysis

Memorandum Generation

• Auto-generated comprehensive investment memorandums

Feedback and Observability

• Integration with Portkey's feedback API for quality monitoring

Getting Started

Prerequisites

• Node.js (v16.x or higher)
• Python (v3.8 or higher)
• npm (Node Package Manager)
• pip (Python Package Manager)
• Google Cloud SDK (for managing Google Cloud resources)

You'll need to set up the following API keys in your environment variables: OpenAI API Key Portkey API Key EXA AI API Key Proxycurl API Key Google Cloud Vision API credentials JSON file

Installation

1. Clone the Repository

git clone https://github.com/danielp1234/memo-generator.git
cd memo-generator

2. Install Node.js Dependencies

npm install

3. Install Python Dependencies

pip install -r requirements.txt
pip install 'crewai[tools]'

4. Build the Project

npm run build

Set Up Environment Variables

Create a .env file in the root directory and add the following environment variables:

OPENAI_API_KEY=your-openai-api-key
EXA_API_KEY==your-exa-api-key
PROXYCURL_API_KEY=your-proxycurl-api-key
GOOGLE_APPLICATION_CREDENTIALS=./path-to-your-google-cloud-credentials.json
PORTKEY_API_KEY=your-portkey-api-key
PORT=3002
GOOGLE_CLOUD_PROJECT_ID=flybridgememo-generator

Set Up Google Cloud Vision API

• Create a Google Cloud Project: Ensure you have a Google Cloud project. If you don't have one, create it in the Google Cloud Console.
• Enable the Cloud Vision API
  • Navigate to APIs & Services > Library in the Google Cloud Console.
  • Search for Cloud Vision API and enable it.
• Create a Cloud Storage Bucket
  • Navigate to Cloud Storage > Click Create Bucket and Name the bucket (e.g., memo-generator) -Click Create.
• Set Up Service Account Permissions
  • Navigate to IAM & Admin > IAM.
  • Locate your service account (e.g., [email protected]).
  • Click the Edit (pencil) icon next to the service account.
  • Click Add Another Role and assign the following roles:
    • Storage Object Admin (roles/storage.objectAdmin)
    • Storage Object Creator (roles/storage.objectCreator)
    • Storage Object Viewer (roles/storage.objectViewer)
    • Cloud Vision AI Service Agent (roles/visionai.serviceAgent)
• Obtain your Google Cloud Vision API credentials JSON file. Ensure you enable Cloud Vision API
• Place the JSON file in the root directory of the project under file name: cloud-credentials.json

Usage

Development

To start the development server, which runs both the backend and frontend concurrently:

npm run dev

Production

To build and start the production server:

npm run build
npm start

Project Structure

• index.js: The main Node.js server file.
• src/: Contains the React frontend code.
• components/: React components used in the frontend.
• main.py: Python script for market analysis.
• agents.py: Python script defining agents for market research.
• tasks.py: Additional Python script for tasks.
• public/: Contains static assets and the index.html file.
• .env: Environment variables configuration file.
• package.json: Node.js dependencies and scripts.
• requirements.txt: Python dependencies.

System Diagram

• Bellow is diagram that explain the components of the application
• See example output memo Link

License

Released under the MIT License. See the LICENSE file for more details.