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Unifying Indian Mobile & Internet Plans with AI and Graph Databases — (Production-ready, Gemini structured outputs)
Latest   Machine Learning

Unifying Indian Mobile & Internet Plans with AI and Graph Databases — (Production-ready, Gemini structured outputs)

Krishna Kumar S
9 likes
October 5, 2025

Last Updated on October 6, 2025 by Editorial Team

Author(s): Krishna Kumar S

Originally published on Towards AI.

TL;DR

The LLM (Gemini) is used with structured output via ChatGoogleGenerativeAI.with_structured_output(...) to directly return validated Pydantic objects from text files containing plans data. The pipeline then writes the cleaned records into Neo4j.

Unifying Indian Mobile & Internet Plans with AI and Graph Databases — (Production-ready, Gemini structured outputs)

Source: https://www.netscribes.com/ licensed under the Creative Commons Attribution-Share Alike 4.0 International license.

This article discusses the importance of comparing telecom plans from major providers in India, emphasizing the need for a canonical representation of data to discern differences. It outlines the technological approach of employing an LLM for structured outputs, Pydantic for validation, and Neo4j for graph representation, creating a robust framework for managing and comparing these plans effectively across various platforms.

Read the full blog for free on Medium.

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