- SERVICE
- STRG.reason
- MODE
- simulation
- MODELS
- causal + Bayesian
- RESEARCH
- since 2014
Causal AI · Forecasting · Simulation
Shape the future before it happens.
STRG.reason simulates real business scenarios, quantifies risks and evaluates decisions on the basis of actual costs and KPIs — causal AI instead of black-box prediction.
- Causal AI
- Beyond pure prediction
- 70 %
- Forecast relevance
- 40 %
- Procurement cost reduction
- 2014
- AI research started
Forecasts answer the question 'what is likely to happen?'. Decisions need an answer to a different question: 'what happens if we intervene?'. Delivery delays, wrong order volumes and capacity adjustments hit costs, availability and risk — often with consequences that ripple through the entire value chain. Without simulation, decisions stay speculative.
Yuri's Tech Talk
Wir sprechen mit Peter Weiss, CEO der Firma Fulcrum, einem führenden SAP Berater und Partner der STRG.AT Mit Fulcrum bringen wir unser kausales KI Modell STRG.Reason in die Welt von SAP und anderen ERP-Systemen
- 01
Real scenarios instead of theoretical models
Test interventions like supply shortages, site relocations or demand shifts before rolling them out — data-driven experiments instead of gut feeling.
- 02
Costs, risks and impact quantified directly
Decisions are evaluated economically, not just statistically: storage cost, delivery delays, availability, degradation and ROI — on real business KPIs.
- 03
Integrates directly into existing systems
STRG.reason fits into existing system landscapes and is productive within weeks — without classic project overhead.
Decision framework
A decision and simulation framework grounded in real data.
With STRG.reason companies test operational and strategic decisions on the basis of their own data, markets and processes. Instead of isolated forecasts you simulate concrete scenarios and immediately see their economic impact.
- Capture data
- Simulate scenarios
- Test impact
- Derive actions
Download Whitepaper
Typical use cases
Where STRG.reason already delivers impact.
What's inside?
Five building blocks for better decisions.
- R.01
Decision Support & Intelligence
Clarity in complex decisions — a structured decision basis instead of gut feeling.
- R.02
Scenario Simulation & What-if Analysis
Walk through options realistically and evaluate their consequences — before they are rolled out.
- R.03
Risk Management & Uncertainty
Plan for and master uncertainty — risks become visible and measurable.
- R.04
Forecasting
AI forecasting models spot developments early — linked to simulation and decision logic.
- R.05
AI for Business Decisions
Intelligent support, not a black box — explainable to management and stakeholders.
- R.06
LLM Integration
Talk-To-Data mittels RAG zur Steuerung des gesamten Systems in natürlicher Sprache
What can you simulate?
Six typical levers.
- S.01
Production cost
- S.02
Delivery delays
- S.03
Workforce deployment
- S.04
Machine relocation
- S.05
Storage cost
- S.06
Logistikkosten
Measurable impact
What STRG.reason delivers in practice.
- 70 %
Forecast relevance
Forecasts with high relevance for more than 70 % of overall volume.
- Double the efficiency
Low effort, high return
Fast payback thanks to low implementation effort.
- 40 %
Cost reduction
Reduction of avoidable procurement cost by up to 40 %.
Case study
Gabriel Chemie
Real decisions. Real results.
A framework for the planning and simulation of economic processes and resources — forecasts, risk reduction and scenario simulations from real production data.
FAQ
Frequently asked questions
- Is STRG.reason only forecasting?
- No. Forecasting is only the foundation. The real value lies in simulation, decision logic and impact assessment.
- How long does the implementation take?
- From proof-of-concept to integration usually only a few weeks.
- Do we need perfect data?
- Your data doesn't have to be perfect. STRG.reason works with realistic, existing data. If consolidation or cleansing is needed, we are happy to handle that.
- Who is this service for?
- Organisations where decisions have measurable economic consequences — cost, availability, risk or service level. Typical settings: complex supply chains, multiple sites, volatile demand or high planning and coordination effort.
Lesen Sie mehr über unsere Forschungen
STRG.magazine
Let's talk about your use case
Causal-AI simulation for your decisions.
Forecast, simulation or a full decision-framework rollout — we listen and propose a workable starting point. Book a demo slot directly or get in touch by email.