Visible Scale

Systems & Architecture

After the audit we implement the top levers. Clean data layers, redesigned processes, model-agnostic architecture. Investment is clearly defined before kickoff, with milestones.

Model

Clear phases. Clear ownership.

  1. 01 / 04

    1. Audit identifies levers

    From the audit you get three to five concrete levers with EUR figures, effort and risk profile.

  2. 02 / 04

    2. Architecture definition

    We define the data foundation, the processes, the interfaces. Investment is agreed with concrete milestones, before we build.

  3. 03 / 04

    3. We build and integrate

    Production-grade code, monitorable, with audit trail. Built model-agnostic so you can switch models tomorrow.

  4. 04 / 04

    4. We operate and maintain

    On request we also handle ongoing operations. Monitoring, updates, model swaps, scaling.

Risk distribution

What we carry. What you carry.

What we carry
  • Architecture and implementation risk
  • Maintenance and bug fixes for the systems
  • Responsibility for the agreed KPIs and milestones
  • Data protection, NDA, GDPR compliance
  • Tooling licenses during development
What you carry
  • Read access to your tools (Microsoft 365, DATEV, SAP, etc.)
  • Two to three hours of your team's time per week during build
  • Ongoing tooling costs after go-live (e.g. AI APIs, hosting)
  • Leadership sign-off before rollout
  • Agreed investment, paid in clear milestones

Tech Stack

What we build with.

AI Backbone

Anthropic Claude and Azure OpenAI as primary models. Local models for sensitive data, fully within your own cloud on request.

Workflow Engine

Microsoft Power Automate, AWS Lambda, Python services. Production-grade, monitorable, fully audit-trailed.

Data

Postgres, Snowflake, Microsoft Fabric. For DACH compliance: hosting entirely in Germany available.

Integrations

Microsoft 365, Google Workspace, SAP, DATEV, Salesforce, HubSpot, ServiceNow, REST and SOAP, documented and versioned.