Preparing Data for AI and LLMs Integration

woodwatch Vstorm

What does WoodWatch do?

The company was the first in the Netherlands to make affordable wood watches. After starting as a passion project outside of work hours, WoodWatch quickly scaled up into a global phenomenon by proving that eco-friendly fashion accessories don’t have to be boring or mass-produced. They are proud to have built the WoodWatch community worldwide, shipping to more than 100 countries and counting. The founders were listed twice by Forbes, Holland as 30 under 30 and 25 under 25. What’s more, WoodWatch has been named to the FT1000, the Financial Times ranking of Europe’s fastest-growing companies, for the second year in a row, in 2022, reaching position 187. It is good to add that WoodWatch plants one tree for every product sold. So far, they have planted more than 500,000 trees, and their goal is to plant 1 million trees by 2025 (which we fully support in Vstorm)

How did Vstorm cooperate with WoodWatch?

This project aimed to centralize data from different sources in one data warehouse with the Cloud for further analysis, utilizing advanced NLP techniques for deeper insights. The WoodWatch team needed a dashboard to visualize data and make real-time changes to live streaming data. The customer wanted to see the live results so they could make key decisions on pricing, storage, team occupancy, etc. In further stages, this centralized data needed to be synced quickly and made available for further analysis work using AI and Large Language Models for a better-enhanced decision-making process for the leadership team. Another part of our cooperation with Vstorm was based on automating the order process of watches with custom gravers for further manufacturing process.”


By launching the application it enabled us to get better insights on our company data, which made it possible for us to make analyses that were impossible before.

Director, WoodWatch


Business intelligence software is now equipped for integration with AI and LLMs, enhancing decision-making processes and data engineering in e-commerce. This advancement gave Customer teams a bird ’ s-eye perspective of the data that mattered to them and helped them distill the information into actionable insights. Some parts of the app were done automatically, and data was always being sent to the warehouse and shown to business owners. Also, one of the production processes, related to product customization, was rebuilt and automated, which helped to save approximately 80 hours of manual work per month. WoodWatch was able to perform analyses that were not possible before the app came out. The implemented system improved efficiency and sales outcomes over time.

Customer details