Does the neuland.ai HUB read our merchandise management system and our PIM?

Yes. If item and stock data sit in an SQL database, the ready-made SQL connector is often enough; we address PIM, ticketing system and your own systems via API and MCP. Reading happens with the permissions of each role; every write action waits for a human OK.

Does the neuland.ai HUB help with product safety and packaging obligations?

Yes, with your own documents. The neuland.ai HUB checks items against documents such as supplier declarations, test reports or your guidelines, which you provide as knowledge, and cites the source for every statement. The Compliance Agent Handel identifies where evidence is missing; the assessment stays with your legal and compliance department.

Do we have to build the agents ourselves?

No. You start with ready-made agents from the library, such as the Retourenmanagement Agent, and adapt instructions and knowledge to your company. If needed, your business unit builds its own agents without programming; admins make them available to the teams.

What does the neuland.ai HUB cost?

After two free test weeks, pilot and regular operation follow at fixed prices, plus a one-time onboarding fee. We prepare the offer based on your use case, details in the pricing overview.

Does the works council need to approve?

neuland.ai HUB works with permissions per role, and access is logged so that results are traceable. Before launch, you define together with the works council and data protection which roles may evaluate which logs.

How many ready-made agents are there for retail and e-commerce?

The Agent Library shows ready-made agents for this industry, from service requests to store management. Each agent states its task and an efficiency figure from the library; these are figures from the library, not a guarantee. You adopt one or more agents and adapt instructions and knowledge to your company.

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Retail and e-commerce

The reason is somewhere in the system. The agent finds it.

Return, service request, supplier spreadsheet or store report: the agents read merchandise management, ticketing system, product information management (PIM), POS and other systems together and submit a draft, correction or report for approval.

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neuland.ai HUB · Returns

and more systems

The Lina down jacket, item 51-88230, has had a 38% return rate since the start of the season. Why?

Tools chosen automatically

Merchandise management · Returns item 51-88230read
Ticketing system · Keyword fit since Sep 1read
PIM · Size chart item 51-88230read
SharePoint · Supplier specification FW26read
PIM · Change proposalDraft

The jacket mostly comes back because of size: 1,140 returns, mainly with return code 03 “too small” ^[1]. Since September 1, 212 tickets say the same thing: it runs small ^[2]. The PIM still holds the size chart from the previous season, FW25 ^[3]. The FW26 specification lists 2 cm less chest width per size ^[4]. The change proposal is in the PIM as a draft.

[1]Returns item 51-88230 · 1,140 returns
[2]Keyword fit · 212 tickets since Sep 1
[3]Size chart · Version FW25
[4]Supplier specification FW26 · Chest width

Please prepare the feedback to the supplier as well.

Outlook · Feedback to supplier 30882Draft

The draft to supplier 30882 is in Outlook: FW26 measurement chart against FW25, with the 212 tickets as evidence ^[1]. Whether this leads to rework or a credit note is for your purchasing team to settle with the supplier.

[1]Draft to supplier 30882 · Measurement chart and tickets

PIM change proposalItem 51-88230 · WordDraft

done: Return rate 38%, return code 03
done: 212 tickets: runs small
done: Measurement chart FW26 compared with FW25
open: Size note for shop, marketplaces and store app
question: Approval by product data management

Example · A change proposal with sources

The agent pieces together the return reason. From service, warehouse, product data and purchasing.

The case from the chat above, as a document: customer service, the returns warehouse, product data and purchasing each have a clue about the Lina down jacket. The Retourenmanagement Agent puts all four into one change proposal, every statement with its source.

Change_proposal_51‑88230.docx

Draft

PIM change proposal · Item 51‑88230 · Lina down jacket · FW26

Finding: return rate 38% since the start of the season, return code 03 “too small” ^[1]. 212 tickets since September 1 with the same statement: runs small ^[2].

Cause: the size chart in the PIM dates from FW25 ^[3]. The FW26 supplier specification lists 2 cm less chest width per size ^[4].

New size note: runs one size small.

Proposal: adopt the FW26 measurement chart, add the note in shop, marketplaces and store app, send feedback to supplier 30882.

[1]Merchandise management · 1,140 returns

[2]Ticketing system · Keyword fit

[3]PIM · Size chart version FW25

[4]SharePoint · Specification FW26

Stays a draft until product data management gives its OK.

Beyond returns, too

Agents for assortment, pricing, stores and suppliers, too. The numbers are on the table before every meeting.

Sell-through, margin, competitor prices and on-time delivery sit ready in systems such as merchandise management, POS or purchasing. Agents bring them together before category management, pricing and store management decide.

Assortment

Sortimentsanalyse Agent

Before the listing round, the Sortimentsanalyse Agent lays out sell-through, margin and stock per product group side by side and flags candidates for delisting. Your category management decides what stays.

Store

Filialsteuerung Agent

Why is a store below last year? The Filialsteuerung Agent combines POS data, footfall and staff hours per region and names the deviation before regional management asks.

Supplier

Lieferantenanalyse Agent

The Lieferantenanalyse Agent rates on-time delivery, quality defects and return rate per supplier and item. Purchasing takes these figures into the annual review.

Ready in the Agent Library

Ready-made agents for retail and e-commerce. Adopt them and adapt them to your assortment.

From service requests to store management: eight of the ready-made retail agents.

All retail agents in the library

Kundenservice Agent

60%

faster processing

Automates service requests in e-commerce.

RetailService center, e-commerce

Produktdaten Agent

50%

less maintenance effort

Structures and optimizes product information in the PIM.

RetailPIM, e-commerce

Filialsteuerung Agent

60%

less reporting effort

Aggregates store data for transparent performance management.

RetailStore management, management

Retourenmanagement Agent

15%

lower return rate

Analyzes return reasons and optimizes return processes.

RetailE-commerce, Customer Service

Bestandsoptimierung Agent

20%

less overstock

Optimizes inventory levels and reduces tied-up capital.

RetailLogistics, purchasing

Sortimentsanalyse Agent

5 to 15%

higher margin

Analyzes sales, margin and inventory data to optimize the assortment.

RetailCategory management, controlling

Kampagnenanalyse Agent

25%

better campaign performance

Optimizes marketing campaigns based on data.

RetailMarketing, e-commerce

Executive Commerce Agent

60%

less preparation time

Consolidates sales, store and financial data for strategic decisions.

RetailExecutive board, management

Figures are based on comparable projects and are not a guarantee.

What the agent sees and what it doesn't

Tickets contain customer data. They are never used for training.

The Retourenmanagement Agent reads return reasons, tickets and product data; it has no access to payment data or customer accounts.

DeploymentEU or on-premisesTickets, returns data and product data stay in EU data centers or in your own infrastructure, your choice.

TrainingExcludedCustomer data from service and returns, purchasing terms and sales figures are never used to train language models.

PermissionsPer agent and roleTools, data rooms and recipients are defined per agent; every company and every sales channel works in its own tenant.

LogCompleteEvery access to tickets and product data is logged traceably, including for your data protection team.

The ISO 27001 certificate, the data processing agreement (DPA) and the technical and organizational measures (TOMs) are in the Trust Center.

Shop, PIM and merchandise management stay

The correction lands in the PIM. After your OK.

Reading happens from merchandise management, ticket system and SharePoint, for example; writing to the PIM only happens after product data management gives its OK. There are ready-made connectors for Outlook, Teams, SharePoint, SQL databases and more; we connect PIM, ticket system, shop and your own systems via API and MCP as an additional service.

Data from Merchandise management, PIM, Ticketing system, SharePoint, Outlook etc. flows through neuland.ai HUB to PIM, Outlook, Microsoft Teams etc.

What IT and compliance ask first

Six answers before you start. Read with your permissions, checked against your documents.

Yes. If item and stock data sit in an SQL database, the ready-made SQL connector is often enough; we address PIM, ticketing system and your own systems via API and MCP. Reading happens with the permissions of each role; every write action waits for a human OK.
Yes, with your own documents. The neuland.ai HUB checks items against documents such as supplier declarations, test reports or your guidelines, which you provide as knowledge, and cites the source for every statement. The Compliance Agent Handel identifies where evidence is missing; the assessment stays with your legal and compliance department.
No. You start with ready-made agents from the library, such as the Retourenmanagement Agent, and adapt instructions and knowledge to your company. If needed, your business unit builds its own agents without programming; admins make them available to the teams.
After two free test weeks, pilot and regular operation follow at fixed prices, plus a one-time onboarding fee. We prepare the offer based on your use case, details in the pricing overview.
neuland.ai HUB works with permissions per role, and access is logged so that results are traceable. Before launch, you define together with the works council and data protection which roles may evaluate which logs.
The Agent Library shows ready-made agents for this industry, from service requests to store management. Each agent states its task and an efficiency figure from the library; these are figures from the library, not a guarantee. You adopt one or more agents and adapt instructions and knowledge to your company.

Name the item with the most returns. We'll show you where the reason is.

Ideally with your own returns data: tickets, return codes and product data for one item then come together in one picture.

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After your request

01You name an item and the systems that hold its returns
02We show the Retourenmanagement Agent on an item like yours
03We clarify which interface connects PIM and ticketing system