Storytelling Assistant

Overview

A powerful AI-powered tool that helps transform technical content into engaging narratives for different audiences. The system uses a combination of RAG (Retrieval-Augmented Generation) and a custom scoring model to generate and evaluate high-quality pitches.

Key Features

• Multiple Output Modes: Tailored for different audiences including Investor Mode, Conference Mode, and General Mode
• Quality Assessment: Custom ML-based scoring model evaluates pitches on four criteria (Coherence, Consistency, Fluency, Relevance)
• Self-Reflection System: Automatically improves generated content based on scoring feedback
• Adaptive Learning: Multiple generation attempts to achieve quality threshold while maintaining best version

Technical Implementation

The system employs a sophisticated architecture that combines:

• RAG Framework: Retrieval-Augmented Generation for context-aware content generation
• Custom Scoring Model: ML-based evaluation system with 4-20 point scoring scale
• Multi-Modal Processing: Handles different input formats and output requirements
• Iterative Improvement: Self-reflection mechanism for continuous content enhancement

Impact & Applications

This tool addresses the critical need for effective science communication by:

• Bridging the gap between technical expertise and audience understanding
• Enabling researchers to communicate their work more effectively
• Supporting entrepreneurs in crafting compelling pitches
• Improving accessibility of complex technical concepts