← All case studies

AI & automation · Commerce operations

E-commerce AI Data Pipeline

Client: CSR Informatics (Germany)Duration: 2023–2024Team: 4 engineers

Sevendyne built an e-commerce operations engine with AI-assisted catalogue ingestion—Rails and Python pipelines that turned heterogeneous product data into repeatable operator dashboards instead of manual spreadsheet wrangling.

Industry & context

What the client needed

Operators needed catalogue intelligence at scale: extract, transform, and present e-commerce data from heterogeneous sources with cost-controlled AI-assisted ingestion and a maintainable back office beyond template storefronts.

Architecture & stack

How we delivered

We delivered a Ruby on Rails dashboard for operator workflows, Python scripts for extraction, transformation, and scraping orchestration, and OpenAI-assisted parsing where structured prompts outperformed brittle selectors alone. SQL Server backed efficient storage and reporting; complementary Spree/Rails marketplace patterns supported AI catalogue import with background jobs and governed release milestones.

Ruby on RailsPythonOpenAISQL ServerSpreeETL / scraping

Outcome

Sevendyne delivered a year-long programme with sustained Rails + Python pod delivery—giving operators a custom back-office engine and AI pipeline pattern for teams outgrowing off-the-shelf commerce tooling.

Schedule a Technical Review