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Diagram
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Initial Page
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Output Example
Inspiration
Pick with Intelligence was born from the idea of making data-driven decisions more intuitive. In the airline industry, demand forecasting often relies on complex tools or manual reports. We wanted to create a system where anyone — even without technical expertise — could simply ask for insights in natural language and get accurate, AI-generated predictions
What it does
The project combines a Large Language Model (LLM) for interpreting user input with a Neural Network that predicts product quantities for flights within a selected date range. This structure allowed us to connect natural language understanding with predictive analytics, creating an intelligent end-to-end workflow.
Challenges we ran into
The biggest challenge was ensuring that the LLM interpreted user queries correctly and that the model received clean, structured data for prediction. Finding the right balance between language flexibility and data precision was key to achieving reliable results
What we learned
->Design communication between frontend, backend, database, and AI models.
->Integrate an LLM with structured function calls in Python.
->Prepare and filter datasets dynamically for neural network evaluation.
