HomeCzech operationsData automation

Czech packaging data automation

Turn Czech orders into packaging figures you can check.

Your e-shop or logistics data already tells part of the story. We can connect it to a packaging catalogue, bring uncertain records to your attention during the quarter and prepare a traceable calculation for the required report. The exact workflow is designed around your systems and source data.

One connected workflow

During the quarter

Import, map and review dispatched Czech orders.

When something changes

Flag gaps in packaging or order data for a person to resolve.

After quarter end

Reconcile, approve and prepare the official report.

Regular data checks can reduce the rush at quarter end. The report still uses actual records from the completed period.

How the process works

From source records to an approved report.

01

Bring in the source records

Use agreed exports or an integration from the shop, marketplace, ERP or logistics provider. Keep the original records and identify orders actually dispatched to Czechia.

02

Map the packaging

Connect products and shipment types to a checked catalogue of packaging components, materials and unit weights. Record changes as packaging evolves.

03

Review exceptions as they appear

Flag missing SKU mappings, changed box sizes, returns and conflicting records. The seller or logistics partner confirms what happened before figures are accepted.

04

Close and approve the quarter

Reconcile the period with dispatch or accounting totals, review the calculation and approve the reporting figures before the EKO-KOM submission.

What we need to begin

Start with a sample, not a system overhaul.

Send a small, representative sample in its original language. We first establish which records can be trusted, what packaging information is missing and whether files or a direct connection make sense. A logistics partner can provide consolidated dispatch data if it identifies each producer separately.

Integration setup and maintenance are scoped and priced after this review. They are separate from the producer's EPR representation and EKO-KOM charges.

Useful starting inputs

  • A sample order or dispatch export, with status and destination fields
  • A product list or SKU identifiers and known packaging variations
  • Packaging component weights and how they were measured
  • The person who can confirm exceptions and approve the quarter

An illustrative example

A seller with several box sizes.

Suppose a seller ships home goods to Czech customers. The order export lists products and destinations; the warehouse record shows which box and filling were used. We connect those fields to a packaging catalogue. An unfamiliar SKU or new box size goes into a review list instead of silently entering the totals.

The team can check that list throughout the quarter. After the quarter closes, it checks the final dispatch totals and approves the figures for the EKO-KOM report. This example describes a possible workflow, not an existing client implementation.

The reporting boundary

Automation prepares the figures. People approve them.

The data flow can run at agreed intervals, while packaging reporting concerns the completed quarter. We keep the source exports, catalogue versions, corrections and approval trail available for review. The producer remains involved where a packaging fact or disputed record needs confirmation.

EKO-KOM publishes the current quarterly report files and instructions on its official reporting page.

A clear next step

Show us one sample of your Czech order or dispatch data and the packaging information you already maintain. We will map the missing pieces and propose a realistic pilot workflow.

Discuss a pilotRead the packaging data guide

Technology stack

We choose technology to fit the goal of each project

We are not tied to a single vendor. For each project, we select suitable AI models, automation and infrastructure, then connect them into one practical solution.

AI, automation and development

  • GoogleGoogle
  • ChatGPTChatGPT
  • ClaudeClaude
  • DeepSeekDeepSeek
  • LM StudioLM Studio
  • GitHubGitHub
  • n8nn8n
  • NotionNotion
  • VercelVercel
  • CloudflareCloudflare
  • MetaMeta

Hardware and AI servers

  • NVIDIANVIDIA
  • AMDAMD
  • ASUSASUS
  • LenovoLenovo
  • HPHP