Simulation · Machine Learning · Queueing
Turn process data into better operational decisions.
SiMLQ’s patented technology builds data-driven simulations of your operation, so you can compare interventions and their performance outcomes before committing to them.
- Patented
- Hybrid queue mining and machine learning
- Digital twins
- Comparative and prescriptive scenario analysis
- Proven
- Validated on real hospital and cloud data
The decisions we support
We tackle the management of highly uncertain service and manufacturing processes.
These are the questions SiMLQ helps management answer — with evidence from their own operational data, not intuition.
Process Improvement
What impact can be expected from actions taken to improve current processes?
Resource Management
How can we relieve system bottlenecks by improving the usage of existing resources?
Financial and Operational Decision Making
How can we make smarter decisions by simulating real-world outcomes before implementation?
Product demo
See SiMLQ test a decision before implementation
Build a data-driven model, compare an operational intervention, and see its expected impact before acting.
See how SiMLQ builds confidence in a digital twin, tests an operational intervention, and compares its expected impact before implementation.
Where we work
One engine, applied where congestion costs the most.
Why SiMLQ
Rigor from research, built for operational reality.
SiMLQ automatically generates process simulations from event data. Our ability to model congestion, and to focus on comparative and prescriptive analytics, is what separates us from conventional process mining.
Our clients
Affiliations & support
Ready to turn your process data into action?
Reach out to see how SiMLQ can unlock the full potential of your processes.