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← ALL CASE STUDIES

RETAIL · DACH · CONFIDENTIAL · E-COMMERCE

E-commerce scale-up: new platform plus embedded remote engineering team

How we combined a focused platform rebuild with a dedicated team model—ways of working, ownership, and metrics that matter for scale-ups.

21 AUGUST 2026·7 MIN READ

CHALLENGE

Replace a limiting legacy stack and grow engineering capacity without long local hiring cycles.

OUTCOME

New platform live in four months; ongoing capacity through a dedicated remote squad.

WEB DEVELOPMENTREMOTE IT / DEDICATED TEAMDEVOPS ALIGNMENT
4 monthsMVP TO PRODUCTION
E-commerce shopping experience on a tablet

CASE STUDY

E-commerce scale-up: new platform plus embedded remote engineering team

Filed under retail · dach · 7 min read.

Rapid growth had outpaced the existing storefront and admin tooling. The client needed a modern commerce stack, better performance for SEO and conversion, and more engineering throughput—but Germany’s hiring market meant months-long delays for each role.

Scope and sequencing

We split work into a customer-facing storefront MVP and parallel tracks for catalogue, promotions, and integrations. Cutting scope for v1 was explicit: launch something merchants could sell on, then iterate on back-office efficiency.

Team model

A small Torq squad (full-stack and frontend-heavy) operated as an extension of the client’s product org: shared sprint cadence, shared Slack channels, and code ownership in the client’s repos. That reduced the “vendor wall” effect that kills velocity in many outsourcing setups.

Engineering practices

CI pipelines, preview environments, and feature flags reduced release risk. We documented API contracts with their ERP partner early to avoid integration thrash in the final month.

Results

  • Production launch in approximately four months from kickoff for the defined MVP.
  • Sustained velocity post-launch through the same embedded team—no re-onboarding cliff.
  • Foundation for international expansion (localisation, payment methods) without another rewrite.

PLANNING SOMETHING SIMILAR

Reuse the pattern — not the timeline.

This overview reflects delivery patterns we use with teams in retail · dach and adjacent sectors — balancing speed, risk, and maintainability. Names and figures are adjusted where needed, but the engineering and collaboration lessons are representative of how we work.

If you are comparing partners for mobile, web, AI, or API work, start with the relevant service page for scope models and FAQs, then use the contact form to share constraints. We will suggest a proportionate next step rather than a one-size-fits-all proposal.

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From the blog

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Engineering leads report folding risk classification and model cards into the same pipelines as security scans. The goal is provable traceability without blocking every experiment.

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DISCUSS A SIMILAR PROJECT

Take this pattern further with our team.

Talk to an engineerExplore services →

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