Use case

Optimizing Supply Chain Logistics

In this demo, PuppyGraph navigates a complex supply chain to optimize logistics and sales performance. We illustrate how to identify top-selling products and verify their inventory status, ensuring they are adequately stocked. Additionally, the demo addresses products with no sales, providing insights into potential market adjustments. It also showcases strategic reallocation of resources, offering solutions for transferring necessary parts from the nearest inventory when they are urgently needed at specific locations. This holistic view facilitates efficient management of supply and demand within the supply chain.

Tech stack

PuppyGraph
Docker
Amazon Redshift

Queries in natural language

  • Which products have the highest sales in the last couple of days?
  • Inventory checks for top-selling products to ensure they are in stock
  • Which products don’t have any sales?
  • Solutions for reallocating parts from the nearest available location when they are needed at a specific site (e.g., in CA) but are out of stock

Want to try it yourself?

We've open-sourced the sample dataset, graph schema, and graph queries on GitHub, so you can recreate this demo in your own environment.

Visit GitHub Repository

Downloads

Sample dataset

Download

Schema JSON file

Download

Query groovy file

Download

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Based on the Memory and CPU of the server that runs PuppyGraph.
  • 30 day free trial with full features
  • Everything in Developer + Enterprise features
  • Designed for production
  • Available via AWS AMI & Docker install
* No payment required

Developer Edition

  • Forever free
  • Single noded
  • Designed for proving your ideas
  • Available via Docker install

Enterprise Edition

  • 30-day free trial with full features
  • Everything in developer edition & enterprise features
  • Designed for production
  • Available via AWS AMI & Docker install
* No payment required