Pimcore work that starts with the data model
We take Pimcore when product data, assets, or multi-channel publishing need a written model. Migrations and greenfield installs share one rule: scope the objects before the UI.
- PIM/DAM models tied to how teams publish today
- Migrations with cutover and ownership maps
- GDPR and processor decisions in the same brief
Data-first delivery, not demo theatre
Pimcore projects fail when the UI ships before classes, workflows, and ownership are agreed. We lock the object model, channels, and success metric before frontend polish.
If a CMS without PIM depth fits better, we say so early. Compare TYPO3, Drupal, and WordPress when the job is primarily editorial pages.
Data quality rules belong in Pimcore workflows before any spreadsheet cleanup after export. We define required fields and approval steps early.
What we check before a Pimcore engagement
- Data object modelClasses, relations, and workflows that feed the storefront or portal are documented first.
- Asset and DAM useHow marketing stores and reuses assets is checked so the DAM stays structured for reuse.
- Integration contractsERP, PIM sync, and API consumers get owners, SLAs, and failure alerts in writing.
- Upgrade and hostingPimcore version, PHP runtime, and hosting constraints are aligned with the delivery plan.
Selected work with commercial stakes
Relaunch study before vendor lock-in
Requirements, localisation, and vendor-scope advice for a multi-market manufacturer relaunch.
Four-market stack under one TechOps lead
Fractional CTO across vegconomist markets plus Cultivated-X: updates, adops, performance, and incident response.
Discovery and launch on a production stack
User interviews ran in parallel with the build so the site matched what buyers asked for.
From brief to a Pimcore release you can run
Data and outcomes
Products, assets, channels, and the metric that decides whether the cycle succeeded.
Model and ownership
Classes, workflows, hosting, and who maintains Pimcore after launch written down.
Engineering cycle
Build against the model. Custom bundles stay documented; unused integrations leave the stack.
Integrations and GDPR
ERP, shop, or CDN hooks with processors and a written data map.
Launch and handover
Staging QA, cutover checklist, and a short runbook for editors and ops.
Pimcore work we take on
PIM/DAM modelling
Object classes and workflows that match how product and marketing teams publish today.
Modernisations of existing Pimcore
Upgrade paths, bundle cleanup, and performance fixes without a fake big-bang rewrite.
Greenfield Pimcore installs
New platforms with written scope for data, channels, GDPR, and hosting before build.
Migrations onto Pimcore
Move product data and assets with cutover plans and URL strategy where a web channel applies.
When Pimcore is the right call
- Product data or DAM complexity is the real bottleneck and needs a data plan
- You need a scoped migration or modernisation with clear owners
- You want GDPR and integration decisions written before build
- You only need a marketing brochure and have no product-data owner
- You expect unlimited hourly modelling without release criteria
- You want “market leader” claims instead of a data and cutover plan
Pimcore questions
Do you migrate product data into Pimcore?
Yes. We map sources, classes, and cutover before import work. Open-ended data projects without exit criteria are a poor fit.
Pimcore or a classic CMS?
Do you build greenfield Pimcore platforms?
Yes, when the data model and ownership justify it. We write channels, roles, and GDPR constraints before the first custom bundle.
How do you handle GDPR on Pimcore?
Processors, retention, and personal data in product or customer objects sit in the build scope. We document vendors and keep consent behaviour explicit where web channels apply.
Where are you based?
Registered in Wiesbaden. Discovery and reviews can happen in person in the Rhein-Main region; delivery runs in structured cycles.
What do you finish in week one on Pimcore?
Data quality rules, required fields, approval workflows, and which systems consume the catalog.
Is spreadsheet cleanup after export acceptable?
Quality rules belong in Pimcore workflows with clear owners. Spreadsheet cleanup after export is a stopgap.
Nearby stacks and services
Technologies: WordPress, Shopify, WooCommerce, Webflow, TYPO3, Drupal, Next.js, React, Frontend engineering, Laravel, PHP, Angular. All technologies →
Services: Websites & WordPress, WordPress agency, SEO for B2B, AEO & GEO for AI search, Website relaunch, Technical compliance, AI & automations.
Office in Wiesbaden
Hans-Böckler-Str. 76
65199 Wiesbaden
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