Inspiration
We were inspired by the growing gap between the amount of information available to researchers and students and their ability to analyze it efficiently. Important insights are often distributed across images, documents, text, and datasets. We wanted to build a system that could understand these different forms of information together rather than treating them separately.
What We Built
We built NexusAI, a multimodal and agentic AI platform that can understand images, PDFs, text, and structured datasets and reason across them to generate meaningful insights.
Instead of acting as a simple chatbot, NexusAI uses an AI agent to determine which tools are required for a user's request. It can perform document understanding, visual analysis, data analysis, knowledge retrieval, visualization, and report generation as part of a single workflow.
How We Built It
The system combines multimodal AI, RAG, Python-based data analysis, and an agentic workflow. Users can upload different types of information and ask questions in natural language. The agent analyzes the inputs, selects the appropriate tools, combines the results, and presents the findings through an interactive dashboard.
We focused on creating a clean, practical interface so that complex AI analysis can be performed without requiring users to have advanced technical knowledge.
What We Learned
Through this project, we learned how multimodal AI can combine different information sources and how agentic systems can dynamically select tools instead of following a fixed pipeline. We also gained experience in connecting AI models with document processing, computer vision, data analysis, retrieval, and visualization.
Challenges We Faced
One of our biggest challenges was making different modalities work together reliably. Images, documents, and datasets require different processing approaches, so designing a workflow that could bring their outputs together was challenging.
We also focused on making the system useful beyond a basic AI demo by adding explainable results, visualizations, evidence, and automated reporting.
Future Scope
We plan to extend NexusAI with more specialized AI agents, additional domain-specific datasets, real-time external data sources, stronger reasoning capabilities, and support for more advanced research and decision-support workflows.
Our goal is to evolve NexusAI into a practical multimodal AI assistant that can help people turn complex information into actionable knowledge.
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