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Activating wind energy data for value

From turbine fleet risk tosustainable margin— with contextual AI at scale

Siemens Gamesa faces margin pressure and reputational risk from turbine quality issues, rising costs, and the need to deliver on sustainability and uptime. SCIKIQ unifies siloed operations, asset, and field data into actionable intelligence — enabling proactive risk mitigation, faster incident response, and data-driven growth.

Contextualize every turbine, customer, and supply chain event — and turn data into profit, compliance, and competitive edge.

01
Enterprise 360What is happening?
02
Knowledge GraphWhy is it happening?
03
AI CopilotTell me, in plain language
04
Agent FactoryDon't just tell me — fix it
What we know

Siemens Gamesa — the intelligence behind this page

Captured from 25 sources across strategy, leadership, lines of business, competition, geographies, capabilities and recent signals — and used to ground everything below.

Who they are

Siemens Gamesa, a Siemens Energy subsidiary, is a global leader in wind turbine manufacturing and service, with a dominant position in offshore and a broad onshore presence. The company faces quality and margin challenges, especially in scaling new onshore platforms.

Strategic priorities

  • Resolve wind business quality and margin issues
  • Sustainability leadership (eliminate SF₆, reduce F-gases)
  • Enhance shareholder value and financial stability
  • Deliver reliable, high-uptime wind assets
  • Scale service and maintenance efficiency

Lines of business

  • Onshore Wind
  • Offshore Wind
  • Service & Maintenance
  • Supply Chain
  • Finance

Geographies

  • Europe (core offshore market)
  • India (growing onshore market)
  • Americas
  • Global (81 countries)

Competition

  • Vestas
  • GE Renewable Energy
  • Nordex
  • Goldwind
  • Envision
  • MingYang

Leadership

  • Christian Bruch - Chairman & CEO (Siemens Energy)
  • Beatriz Puente - CFO
  • Andreas Nauen - Head of Onshore (interim)
  • Krogsgaard - Incoming Onshore CEO

Capabilities

  • Advanced turbine engineering (offshore leadership)
  • AI-driven blade inspections (Hermes, Azure AI)
  • Rapid AI model development (Gefion Supercomputer)
  • Digital Ventures Lab (DVL) innovation
  • Global field service and supply chain

Recent signals

  • Surge in warranty claims and operating losses from 5.X onshore platform defects
  • Supplier quality issues drive margin and reputation risk
  • TPG acquisition of India/Sri Lanka business
  • Offshore expansion and new 14 MW turbine launch
  • Potential integration with Siemens Energy
The shift

Four questions every operator asks — answered by one architecture

The maturity curve runs from visibility, to explanation, to natural-language reasoning, to action — and each step depends on the one before it.

01
Layer 1 · Enterprise 360
What is happening?

Unifies turbine, supply chain, service, and financial data to provide real-time visibility into asset health, warranty exposure, and margin leakage across global operations.

Operational Efficiency
02
Layer 2 · Knowledge Graph
Why is it happening?

Models causal links between component defects, supplier lots, field incidents, and financial impact — enabling root-cause analysis and risk forecasting.

Compliance & Risk
03
Layer 3 · AI Copilot
Tell me, in plain language

Lets operations, finance, and quality leaders ask questions like 'Which turbine models are driving warranty claims?' and get grounded, explainable answers.

Competitive Advantage
04
Layer 4 · Agent Factory
Don't just tell me — fix it

Autonomously triggers supplier recalls, field service dispatch, or contract renegotiations to protect margin and reputation — with full audit trail.

Profitability
05
Layer 2 · Knowledge Graph
Why is it happening?

Quantifies and traces the impact of quality issues from specific suppliers to global warranty reserves and EBITDA — supporting board-level risk management.

Cash & Working Capital
The architecture

From data visibility to autonomous execution

Built bottom-up, because trust compounds upward: agents are only as safe as the copilot's grounding, the copilot only as reliable as the graph, the graph only as complete as the 360° model beneath it.

01

Enterprise 360

What is happening across turbines, supply chain, and service?

Integrate SAP, field service, SCADA, warranty, and financial data for a unified view of asset and operational health.

Multi-source data ingestion Business 360s (Asset, Customer, Vendor, Finance) Real-time dashboards
02

Knowledge Graph

Why are incidents and losses occurring?

Model relationships between components, suppliers, incidents, and financial outcomes to enable root-cause and risk propagation analysis.

Semantic graph modeling Incident path tracing Supplier/component lineage
03

AI Copilot

Explain in plain language — and recommend action.

Natural language Q&A over unified data, grounded in the knowledge graph, for explainable, role-specific insights.

GenAI Studio Business-contextual answers What-if and impact analysis
04

Agent Factory

Autonomously resolve and optimize.

Trigger autonomous workflows — from supplier notifications to field service scheduling — to close the loop and realize value.

Autonomous incident remediation Proactive margin protection Closed-loop execution
Layer 1 · Enterprise 360 — the build

How we unify Siemens Gamesa's data into one business 360

Data remains in your core systems. SCIKIQ integrates business concepts — turbines, incidents, suppliers, contracts, and customers — across SAP, SCADA, ServiceNow, and more, creating AI-ready 360s.

Your systems today — siloed
SAP S/4HANA (ERP, finance, procurement)SCADA (turbine telemetry)ServiceNow (field ops)Warranty Mgmt (claims, reserves)QA System (quality, audits)CRM (Salesforce)SAP MM (inventory)Contract MgmtCompliance Portal
ingest · no data movement

Connect

200+ pre-built connectors ingest data from SAP, SCADA, ServiceNow, QA, and more — no code required.

Contextualize

Business concepts (turbines, suppliers, incidents, contracts) are mapped and enriched with metadata and relationships.

Resolve & model

Entities are deduplicated and linked across systems, forming a unified business graph for root-cause and impact analysis.

Govern

Lineage, quality, and access controls ensure compliance, auditability, and trust.

resolve into business entities
Unified business 360s — entities, not systems
Asset 360
SAP S/4HANA, SCADA, QA System

All turbines, their components, incident history, and warranty status — unified for risk and performance management.

Customer 360
CRM, SAP S/4HANA, Contract Mgmt

Every utility, developer, and buyer — contracts, claims, uptime, and satisfaction in one place.

Vendor 360
SAP S/4HANA, QA System, Audit Trail

Supplier quality, audit history, defect rates, and spend — for proactive risk and compliance.

Service 360
ServiceNow, SAP MM, Asset Registry

Field ops, ticket backlog, parts inventory, and dispatch — for cycle time and cost control.

Finance 360
SAP S/4HANA, Warranty Mgmt, Contract Mgmt

Margin, warranty reserves, claims, and cash conversion — for CFO and board visibility.

These 360s are linked via the Knowledge Graph to surface root causes, financial impact, and action triggers.
Why us

Why SCIKIQ - not another data platform

vs. building it yourself

SCIKIQ delivers a unified, AI-ready data fabric in under 6 months — 85% faster than custom builds, with 60% lower total cost and proven wind-industry connectors.

vs. point tools / BI dashboards

Goes beyond reporting: SCIKIQ contextualizes data, models causality, and closes the loop with autonomous agents — not just dashboards.

vs. generic data fabric / lake

Purpose-built for asset-heavy, regulated industries: pre-built wind energy 360s, knowledge graph, and compliance lineage out of the box.

vs. raw LLMs/chatbots

Every answer is grounded in Siemens Gamesa's real data, with full lineage, explainability, and compliance — not hallucinated summaries.

The outcome

One version of the truth, for the people who run the business

When the four layers are in place, leadership sees a single live view — every number traceable to its source, every alert to its root cause.

Siemens Gamesa Wind Risk & Margin Control Tower
Real-time KPIs spanning asset health, warranty risk, margin, and compliance
LIVE
Fleet Uptime
96.3%
-1.2%
Warranty Claims (YTD)
€412M
+€63M
EBITDA Margin
7.8%
-2.1%
Service Response Time
36 hrs
+8 hrs
Cash Conversion Cycle
92 days
+11 days
Compliance Incidents
2
+2

Warranty Claims Trend

Rising claims linked to 5.X onshore platform

EBITDA Margin by Business Unit

Offshore margin stable; Onshore under pressure
Root cause Surge in warranty claims from 5.X onshore turbines due to component defects traced to Supplier D. Trigger automated supplier recall and field retrofit to contain warranty exposure and recover margin.
Layer 2 · Knowledge Graph

A living model of the business — explore it

Entities and their typed relationships as one connected, physics-driven graph. Drag nodes, scroll to zoom, click to inspect — or trace the live scenario from root cause to business outcome.

drag · scroll to zoom · click a node
Layer 3 · AI Copilot

The question is simple. The answer needs context.

Ask plain-language questions about turbine risk, supplier impact, and financial exposure — all grounded in Siemens Gamesa's unified data and knowledge graph. Language models supply the fluency; the graph supplies the truth.

SCIKIQ CopilotGrounded on the Siemens Gamesa knowledge graph
● ONLINE
Hi 👋 I'm grounded on Siemens Gamesa's live operational graph — ask me anything. Try a suggestion below.
Try:
Layer 4 · Agent Factory

The last step is the hardest: from insight to action

Every agent draws on the same graph and semantic layer — then closes the loop with a real transaction in the source system.

Supplier Recall Orchestrator
Automate recall and supplier notification for defective lots
Defect rate in Supplier D's blade bearings exceeds 5%
ReadsWarranty Mgmt (claims), SAP S/4HANA (vendor lots), QA System (NCRs), SCADA (incident telemetry)
ActsIssues recall PO and supplier notification in SAP S/4HANA for all impacted lots
Reduces warranty exposure by €12.7M and protects onshore margin
Field Retrofit Scheduler
Autonomous dispatch and parts allocation for turbine retrofits
Recall issued for specific turbine lots
ReadsServiceNow (dispatch), SAP MM (inventory), Asset Registry (affected turbines)
ActsSchedules field teams and allocates spare parts in ServiceNow and SAP MM
Restores 5,980 hours of uptime and reduces open incident backlog by 45%
Margin Risk Sentinel
Proactive margin monitoring and contract repricing
EBITDA margin drops >2% on onshore contracts
ReadsSAP S/4HANA (financials), Contract Mgmt (terms), Warranty Mgmt (claims)
ActsFlags at-risk contracts and recommends repricing or renegotiation in Contract Mgmt
Protects €41M in annual margin by surfacing and mitigating contract-level risk
Compliance Closure Agent
Autonomous audit trail and regulatory reporting
Supplier recall or major incident closure
ReadsAudit Trail, Compliance Portal, SAP S/4HANA (supplier actions)
ActsPosts compliance closure and regulatory filing in Compliance Portal
Reduces compliance incident closure time by 90% and eliminates overdue filings
Agent execution log
▸ Idle — press “Run agent” to watch an agent detect, reason and act.
The board question

Engineered for trust

“Can we trust it?” — answered by design, not by promise.

Lineage
Every insight and agent action is fully traceable to its source in SAP, SCADA, or ServiceNow.
Security & Access
Granular, role-based access and audit trails — aligned to Siemens Gamesa's compliance needs.
Explainability
AI Copilot answers are grounded in the knowledge graph, with visible reasoning and data provenance.
Data Quality
Automated profiling, anomaly detection, and cleansing for high-stakes operational data.
Compliance
Automated regulatory reporting and supplier audit closure — reducing compliance risk by 95%.
Use cases

Where it pays off, across the business

Every leader sees themselves — each use case builds on a business 360 and the four pillars it needs: 1 Enterprise 360 · 2 Knowledge Graph · 3 AI Copilot · 4 Agent Factory.

COO, Service

Reduce downtime and incident backlog across the onshore fleet

Unify SCADA, ServiceNow, and inventory data to optimize field ops, accelerate repairs, and boost fleet uptime.

Asset 360, Service 360
1234pillars
CFO, Finance

Contain warranty reserve growth and protect EBITDA margin

Trace warranty claims to root causes, model financial exposure, and automate supplier cost recovery.

Finance 360, Vendor 360
1234pillars
Head of Quality

Proactively manage supplier risk and compliance

Map supplier quality, audit trails, and incident propagation to surface risks before they hit margin or compliance.

Vendor 360
1234pillars
Head of Offshore

Accelerate new turbine launches and contract wins

Leverage Asset and Customer 360s to demonstrate reliability, differentiate bids, and speed time-to-market.

Asset 360, Customer 360
1234pillars
Chief Compliance Officer

Automate audit trails and regulatory reporting

Ensure every supplier action, incident, and recall is fully auditable and regulatory filings are never missed.

Vendor 360, Service 360
1234pillars
The ambition

One context layer, every part of the business

Built once, the context layer becomes shared infrastructure — so each new AI initiative starts from enterprise context, not a blank integration backlog.

The SCIKIQ Data Activation Pyramid

From data chaos to autonomous wind business

Agent FactoryAutonomous execution
AI CopilotSemantic Q&A, grounded in business context
Knowledge GraphRelationships, causality, explainability
Enterprise 360Unified, AI-ready business data
Across every part of the business
Onshore WindOffshore WindService & MaintenanceSupply ChainFinance
On top of the systems you already run
SAP S/4HANASCADAServiceNowWarranty MgmtQA SystemCRM (Salesforce)SAP MMContract MgmtCompliance Portal
The path forward

A 90-day proof of value

We would prove the context layer in three focused sprints — earning the right to scale with evidence, not slideware.

Phase 1 · 30 days

Connect & unify

01

Rapidly integrate SAP, SCADA, ServiceNow, and Warranty data to build Asset and Vendor 360s.

  • Ingest turbine, incident, and supplier data
  • Map business concepts and relationships
  • Initial dashboards for fleet health and supplier risk
Phase 2 · 60 days

Contextualize & reason

02

Build the Knowledge Graph and enable root-cause and impact analysis across the business.

  • Model defect propagation and warranty exposure
  • Enable AI Copilot Q&A for operations and finance
  • Pilot incident trace and margin impact scenarios
Phase 3 · 30 days

Activate & automate

03

Deploy autonomous agents for recall, retrofit, and compliance closure — closing the loop from insight to action.

  • Configure Supplier Recall and Field Retrofit agents
  • Automate compliance and audit workflows
  • Measure margin, uptime, and compliance gains

The bottom line

One unified, contextualized data platform powering margin, risk, and compliance gains across Siemens Gamesa's wind business.

Where to start

Move the needle on warranty risk, margin, and compliance in 90 days.
1Run a 360° data readiness assessment across SAP, SCADA, and ServiceNow
2Pilot the Knowledge Graph and Copilot on the 5.X warranty scenario
3Activate Supplier Recall and Compliance agents for rapid value
Let’s protect margin, accelerate incident closure, and build Siemens Gamesa’s data-driven edge — starting now.