Does AI invent missing technical specifications?

No. Technical attributes come from agreed sources or documented conversions. If evidence is missing, the field remains empty or is flagged. Draft marketing copy is kept separate from confirmed attribute values.

How does this differ from document processing?

Document processing extracts fields from documents. Product data processing adds item identification, consistent attributes, units, conflict checks and repeatable record maintenance.

Can ETIM and ECLASS be supported?

Yes, after agreeing versions, required classes, usage rights and expert approval. Classification suggestions are not a promise of correct assignments across arbitrary product groups.

How are duplicates handled?

Unique identifiers and agreed comparison fields identify potential duplicates. Uncertain merges require approval so distinct variants are not accidentally combined.

Can the records support the quotation assistant?

Yes. Approved items and current pricing sources can support it. Historical invoice prices and current sales prices remain separate data with their own validity.

Does our product data leave the company?

Not necessarily. Processing can run on-premises or on servers in German data centres. We decide which model is used and where it runs before the pilot.

How much does AI product data processing cost?

The pilot costs from €17,900 excl. VAT for one product group with up to 30 attributes and one export path. We check data quality, interfaces and target environment before commissioning; extensions are priced separately.

What happens after the pilot?

The pilot ends with an acceptance report and a recommendation: move to production, extend or stop. You receive the proposal for the production rollout with the pilot's acceptance report, and the pilot price is credited against it; rules, test set and pipeline are reused. Ongoing operations are optional. If the workflow is already clear, implementation can also start directly. Further supplier files in the agreed formats run through the same path; new layouts or product groups are checked for required adjustments.

Process product data with AI: turn supplier data into consistent attributes

Suppliers send PDFs and spreadsheets in their own formats. In the pilot, AI maps this data to your attribute schema, normalises units, flags conflicts and duplicates and prepares the export.

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Starting point

Every supplier sends product data in its own format

Supplier PDFs and spreadsheets are transferred to the attribute schema by hand
Units, names and mandatory fields differ from supplier to supplier
Duplicates and conflicting values only surface in the shop or catalogue
Target attributes and owners for approval can be named

Outcome

Turn supplier files into maintainable product records

After the pilot, supplier files for one product group run through a pipeline into your attribute schema. Your team reviews conflicts and gaps instead of retyping values.

Standardise attributes
Map names and units to the agreed target schema without inventing technical properties.
Check data quality
Route missing required fields, conflicting values and potential duplicates for targeted review.
Process new deliveries
Ingest further files through the same pipeline and review changes against approved records.

Data or integration path still unclear? The AI Opportunity Check evaluates one specific workflow and its prerequisites.

View opportunity check

Pilot scope

A pilot for one product group and target schema

One product group with up to 30 attributes, confirmed input formats, quality rules, one export path and a sample report.

Included

One product group with up to 30 attributes
A bounded data set and approved input formats
One export path, quality rules and approval
Sample report with provenance, conflicts and missing data

Extensions

Scoped separately as needed

Complete catalogue cleansing and unlimited data volumes
New PIM interfaces, translation and additional product groups

Process

From supplier files to an approved export

We start with one product group and real supplier files. Values are taken from sources or converted by rules; if evidence is missing, the field stays empty.

01
Define the dataset
Define the product group, supplier examples, target attributes and data volume.
02
Configure mapping
Extract source fields and map them to the schema, units and item identifiers.
03
Validate quality
Review representative records, including conflicts and gaps, with subject-matter owners.
04
Hand over the import workflow
Test approved exports and train the team to process further supplier deliveries.

What we need from you

Supplier examples and existing item records
Attribute schema, required fields and allowed units
Data volume, update frequency and target system

Scope and investment

Cost of AI product data processing

Starting price for one product group and one target schema. Further product groups, translations or new PIM interfaces increase the scope.

Not sure yet whether the pilot pays off? The AI potential check (from €3,900 excl. VAT) answers that first.

Delivery starts once agreed data, access and stakeholders are available. The binding scope and price are defined in your proposal. Hardware, hosting, model consumption, licences and ongoing operations are quoted separately. Follow-on projects are costed against reusable results. We credit the pilot price when you commission the production rollout; there is no requirement to purchase every stage. A pilot concludes with a quality report and an evidenced recommendation to proceed or stop. A documented no-go is a valid outcome. Production approval and ongoing operations are agreed separately.

All prices are net and exclude statutory VAT. The offers are addressed to businesses.

Product Data Pilot

Map supplier data for one product group to an agreed attribute schema, flag conflicts and export after approval.

from €17,900excluding VAT and separately quoted third-party costs

Credited against the production rollout. You receive the proposal for it with the acceptance report.

4–6 weeks

Scope as described above

Outcome and verification: Reviewable import data and documented quality against agreed reference records.

After the pilot

From pilot to ongoing product data maintenance

The pilot ends with a recommendation: move to production, extend or stop. You receive the proposal for the production rollout with the pilot's acceptance report, and the pilot price is credited against it; rules, test set and pipeline are reused.

AI Quotation Assistant

Use approved items and price sources for quotation drafts.

View offer

AI Document Processing

Extract and validate further document types in structured form.

View offer

Managed LLMOps

Monitor AI components and assess changes; data maintenance is agreed separately.

View offer

Frequently asked questions about AI Product Data Processing

Scope, integration and subject-matter responsibility.

Reviews & projects

What clients say about working with us

From local AI integration to architecture, data sovereignty and ongoing operations.

WZ-IT moved our studio infrastructure from decentralised individual devices to a central platform: every site is securely connected via VPN, new devices are onboarded automatically and an entire site is provisioned from a template, without manual steps on location. What impressed me most is the breadth and depth of their knowledge: Timo and Robin are not a typical IT provider who sets up a server and leaves. The two of them think their way into highly complex infrastructure and software topics, work through every requirement we put in front of them, and build networking, provisioning and operations so that everything fits together in the end. WZ-IT is an excellent partner for complex software, network and architecture projects.

Steve KirchnerManaging Director, nextGYM GmbH

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International

Built in Germany's Ruhr Valley. Running worldwide.

WZ-IT designs, develops and operates infrastructure and software for clients in Germany and internationally. We deliver projects remotely and continue supporting them in ongoing operations after go-live.