Cases · ribbon
Remote Native  /  Cases
Cases

What the AI Operating System delivers —
in three DACH sectors.

Three engagements across Insurance, E-mobility, and Industrial — each anchored in a different plan level. The methodology from the book, applied to real operating constraints. All engagements are confidential.

InsuranceE-mobilityIndustrialSelected engagements
Case 01 · Insurance · Plan 2 Accelerator · Confidential

Claims-review triage as the first workflow.
One KPI, defended at the board.

A mid-size DACH insurance carrier. Claims reviewers spend 40% of their time on triage decisions that follow a deterministic pattern 72% of the time. The use case is obvious — the problem is shipping it.

The constraint isn't the model. It's the integration layer: the claims data sits in a legacy core system that doesn't expose clean APIs, and the compliance team needs an audit trail before they'll sign off on autonomous decisions. Plan 2 Accelerator — 6 weeks, one workflow, one KPI. The triage loop is rebuilt AI-native on a thin data plane that bridges the legacy core without replacing it. Shadow mode for weeks 3–5, then live in week 6.

Plan
2 · Accelerator
DIFM
Duration
6 weeks
Discovery + build + ship
Entry
€50K
DIFM
Target workflow
Claims triage
1 workflow live
Target KPI
Cycle-time
Measured weekly
Status
Confidential
Under NDA

What the 6-week build looks like

KPIs
1 wfshipped to production by week 6
1 KPItriage cycle-time, measured weekly
6 wksdiagnose → live · target window
Case 02 · E-mobility & Energy · Plan 3 OS Build · Confidential

Billing reconciliation + fault triage,
on a shared data plane.

A DACH operator of 3,200 public charging points. Two load-bearing operations run on fragmented tooling: billing reconciliation (CPO-to-MSP handoffs, disputed sessions, refund routing) and field-fault triage (which faults route to a technician, which can be resolved remotely, which need firmware escalation).

These aren't independent problems. Both need the same session-level data plane to work. Plan 3 OS Build — 13 weeks — installs both workflows on a shared data architecture, adds the governance layer (EU AI Act, audit trail), and hands the ops team a console to manage exceptions without engineering support.

Plan
3 · OS Build
DIWM
Duration
13 weeks
Full methodology install
Entry
€80K
DIWM
Workflows
Billing + fault triage
Shared data plane
Governance
EU AI Act baseline
Audit trail, DPIA
Status
Confidential
Under NDA

The 13-week build in three phases

KPIs
3 wflive across 13 weeks
8 cmpof the OS in place at handover
13 wksbook methodology · full install
Modernization · orbital
Case 03 · Industrial · Modernization · Confidential

Stabilize the legacy stack,
then layer AI workflows one at a time.

A German Mittelstand manufacturer. The after-sales operation runs on a 9-year-old booking and spare-parts system. Key-person dependency risk — two people who know how it works. The AI initiative stalled at integration: the models are fine, the stack can't accept them.

This is a Modernization engagement. Not a replatform — a staged migration. Legacy support continues uninterrupted while the replacement gets built. Month 4: first AI-native workflow live on the new plane. Month 6: cutover. Months 7–9: slices 2–3 land on the same stack, each faster than the last because the data plane is already instrumented.

Engagement
Modernization
Expansion engine
Entry
Audit €25K
2–3 weeks
Full migration
€850K
4–9 months staged
Constraint
Legacy stack
AI workflows blocked
Approach
Staged slices
No big-bang cutover
Status
Confidential
Under NDA

The four phases

KPIs
0regressions · target across the migration
+1 wfAI-native, in parallel with stabilization
Staged6-month plan · no big-bang cutover
Selected engagements

Anonymized client work —
across sectors and engagement types.

A selection of engagements delivered under Remote Native and its predecessor operations. Company names withheld by agreement.

AI Operating SystemRetail & E-Commerce · DACH

Leading E-Commerce Group

AI-driven operational restructuring across a core business unit. Workflow automation, data pipeline redesign, and team enablement — resulting in a measured 60% cost reduction in the target operation.

60 %cost reduction · measured
AI Operating SystemE-Mobility & Energy · DACH

DACH E-Mobility Operator

AI readiness assessment across charging infrastructure operations. Full Level 3 implementation roadmap delivered — covering data architecture, workflow prioritization, governance baseline, and build sequencing.

L3 roadmapfull implementation plan delivered
ModernizationIndustrial · Mittelstand

Industrial Tech Platform

Legacy stack modernization for a 9-year-old after-sales system. Staged migration architecture, AI-readiness audit, and operational takeover — clearing the path for AI-native workflows.

Modernizationlegacy → AI-ready stack
AI Operating SystemManufacturing · Global

Global HVAC Manufacturer

QR-code-based redirection tool for global field service management. Built and deployed for international technician operations across multiple markets.

Global rolloutmulti-market deployment
AI Operating SystemE-Commerce · Data

Product Data Company

PIM process optimization workshops. Workflow analysis, bottleneck identification, and process redesign for product information management at scale.

PIM optimizationprocess workshops delivered
Next step

Take the diagnostic.
Find out where your leverage is.

12 questions across the 6 dimensions of the AI Operating System. Scored result, personalised next move, and free ebook in your inbox. Or book a 20-minute Fit Call.

Take the diagnosticBook a 20-min Fit Call