Narratio AI — Business Narrative Deck Generator

My Role

• 01Trained the multilingual sentiment analysis model so the system can understand positive, negative, and neutral signals across multiple languages.
• 02Added an embedding model layer to improve semantic understanding for research context, business signals, and narrative generation.
• 03Designed the AI architecture that connects web scraping, web research, sentiment analysis, embeddings, and LLM-based slide generation.
• 04Planned the web search and research workflow so the platform can collect relevant information from public websites, market reports, and news sources.
• 05Helped transform raw web insights and conversation context into structured signals for business narrative and consulting-style deck generation.

Features

• 01Natural language input for turning user context, raw data, and conversations into structured slide narratives.
• 02AI agent workflow that performs web search research across public sources such as news, market reports, and websites for business context.
• 03BiLSTM sentiment analysis to classify multilingual text into positive, negative, or neutral signals.
• 04Embedding-based semantic layer to improve context matching between research findings, business signals, and slide content.
• 05LLM-powered slide generation to produce polished consulting-style narratives, charts, and recommendations.
• 06End-to-end workflow from research and analysis to modular presentation-ready deck components.

Impact

• Reduces manual research and slide-writing work by turning unstructured information into ready-to-use business narratives.
• Helps teams understand market trends, risks, and opportunities through sentiment signals and AI reasoning.
• Supports data-driven consulting decisions by combining web insights, machine learning sentiment analysis, and LLM recommendations.
• Makes multilingual business intelligence more accessible by processing sentiment across multiple languages.

Stack