JurrasIQ: AI-powered insights for archaeology—predict, classify, value, and examine fossils with foolproof precision
Inspiration
While reading about Hacklytics 2025, the theme of Jurrasic Age intrigued all of us. We realized that people often underestimate the unspoken world of archaeology, and hence we decided to use our project to contribute to the field. We came up with JurrasIQ, the ultimate AI-driven solution to assist archaeologists in recovering the past and preserving history.
What it does
JurrasIQ is an AI-powered platform revolutionizing archaeology through intelligent automation. It accurately predicts archaeological hotspots by analyzing previous discoveries, soil composition, and terrain deduction datasets. Its advanced machine learning model also classifies obtained fossils with a remarkable 99%+ accuracy. Additionally, JurrasIQ features an intelligent market value predictor that evaluates fossil worth based on real-time sales and past transaction data. Furthermore, its agentic AI flow assists in financial and operational planning for future excavations through a comprehensive risk analysis, making archaeological research more efficient and strategic.
How we built it
JurrasIQ is powered by a frontend built using Next.js, ensuring a dynamic and responsive UI and supported on the backend by Node.js, handling data processing and API interactions. We utilized Leaflet.js to visualize excavation sites and fossil discovery locations through heatmaps. We also leveraged MobileNetV2 for fossil classification, providing high accuracy with low computational cost, and we incorporated the OpenAI API for data-driven insights, aiding in fossil valuation and excavation planning.
Challenges we ran into
Dataset Limitations: Finding comprehensive, high-quality datasets for fossil classification and excavation site prediction was challenging. We overcame this by aggregating data from multiple academic sources and training our model with synthetic data augmentation. Optimizing AI for Real-Time Analysis: Balancing model accuracy with real-time predictions was a significant challenge. We fine-tuned MobileNetV2 and optimized backend processes for faster response times. Geospatial Integration: Implementing precise geospatial mapping and ensuring compatibility with terrain datasets required extensive experimentation with Leaflet.js.
Accomplishments that we're proud of
Achieved 99%+ accuracy in fossil classification using an optimized MobileNetV2 model. Successfully integrated real-time market valuation for fossils, providing archaeologists with crucial financial insights. Developed a dynamic excavation planning assistant, improving strategic decision-making in archaeology.
What we learned
The importance of data preprocessing in achieving high ML model accuracy. How to optimize AI models for real-time applications without sacrificing accuracy. The potential of AI in scientific fields like archaeology demonstrates how technology can enhance historical research.
Tracks
Gen AI Track JurassIQ leverages Generative AI to enhance archaeological research through automated excavation planning, AI-powered fossil classification, and intelligent financial modeling. Our agentic AI flow creates structured excavation blueprints, estimating costs, labor, and logistics while ensuring archaeologists receive optimized excavation insights in real time. Using OpenAI’s advanced models, JurassIQ generates precise excavation plans, financial forecasts, and strategic insights, demonstrating the power of Gen AI in transforming historical research and scientific discovery.
Finance Track JurassIQ incorporates AI-driven financial modeling to optimize excavation budgeting and fossil valuation. The system predicts excavation costs, labor expenses, and trip logistics, ensuring financially efficient operations. Additionally, its intelligent fossil valuation engine estimates market prices based on historical transactions and current trends, allowing archaeologists to assess the financial worth of their discoveries. By integrating financial analytics with AI, JurassIQ empowers archaeologists with data-driven decision-making, improving resource allocation and excavation success rates.
What's next for JurrasIQ
Expanding our dataset: Partnering with museums and research institutions to refine our fossil classification model. Enhancing excavation site predictions: Incorporating LiDAR data for more precise terrain analysis. Developing a mobile app: Making JurrasIQ accessible to field archaeologists through an intuitive mobile interface.
Built With
- leaflet.js
- next.js
- openai
- pandas
- python
- tensorflow
- typescript


Log in or sign up for Devpost to join the conversation.