Service

Process design & documentation

Map the as-is workflow, define the to-be automation and produce documentation detailed enough to become the instruction set for implementation.

What we solve

Precise process design before engineering starts.

01 · we handle

As-is and to-be process maps

result

Less ambiguity

02 · we handle

Owner, trigger, edge-case and SLA definition

result

Faster build cycles

03 · we handle

AI-ready technical documentation

result

A roadmap stakeholders can sign off

Deliverables

  • Process map
  • Data contract
  • Acceptance criteria
  • Implementation backlog

Outcomes

  • Less ambiguity
  • Faster build cycles
  • A roadmap stakeholders can sign off

Common integrations

Factory filesCSV · XLSX · XML
PIM APIsproduct · warranty · media
ERP dataorders · serials · production
Service workflowsclaims · lookup · notifications

What you get

Four things, in one engagement.

01

As-is process map

The real flow with every manual step, workaround and bottleneck made visible and owned.

02

To-be specification

Triggers, owners, edge cases and SLAs for the automated flow, agreed with every stakeholder.

03

Data contracts

Field-level definitions of what moves between factories, ERP, PIM and service systems.

04

Acceptance criteria

Testable statements of done, so sign-off is a checklist instead of a negotiation.

Runs onProcess mapsRule tablesAPI contractsAcceptance testsRunbooksBacklogs

Where it sits

From factory export to service-ready record.

Every engagement plugs into the same governed pipeline. This service strengthens its part of the flow without breaking the rest.

Factory filesCSV · XLSX · API
Validaterules per factory
Enrichparts · manuals
PublishPIM · ERP API
Service-readylookup · alerts

Onix x Duscholux

Duscholux warranty data automation

Automated factory warranty and serial number data from four European factories into a PIM-ready operational pipeline.

4factory flows
0manual import steps
14days after production
40%estimated time reduction

Very precise and well documented. Documents were ready to be turned into code. AI support in development is the part that matters. An in-depth process design is key to achieve it.

Client-side project review, Duscholux
Azure Logic AppsAzure App ServiceNext.js admin panelPIM APIEmail notificationsSharePoint / OneDrive

How we deliver

A delivery process designed for messy operational data.

Diagnosis first, scoped delivery second, measurable operation third. That order keeps automation precise instead of decorative.

01

Process triage

Identify systems, owners, file flows, exceptions and the business cost of manual work.

02

Operating spec

Define data contracts, validation rules, enrichment logic, roles and acceptance criteria.

03

Automation build

Implement the workflow layer, integrations, admin panel and notifications.

04

Real-data validation

Test with actual factory exports, edge cases and stakeholder reviews.

05

Operate and expand

Monitor results, improve quality and scale the pattern to more factories and processes.

Service FAQ

Asked on the first call.

More general questions live in the full FAQ.

Because AI-supported development is only fast when the rules are explicit. A rule clarified in documentation costs minutes; the same rule discovered mid-build costs weeks.

Living documents your team keeps after the project: process maps, rule tables, API contracts and acceptance criteria, not a static PDF nobody reopens.

Project triage

Bring the messy process. We will map the path to automation.

Share the workflow, systems and data sources. We turn it into a clear next step: rescue, integration, admin panel, or a fuller automation build.

Reply within 1 business dayNDA-friendly reviewFixed scope before code

Typical first audit

free · senior-led
  • System and file-flow map with named owners
  • Automation opportunity score for each manual step
  • Delivery plan, risk list and a fixed-scope next step
Start project triage