AI Optimisation for Workload Automation
Our AI-driven optimisation helps you streamline your workloads. Map dependencies, surface bottlenecks, and optimise batch scheduling, so workloads run faster, fail less, and lower cost.
Smarter workload automation with AI
Ortom8 AI Optimisation uses AI and process mining to analyse and improve batch scheduling, moving beyond manual monitoring and static tuning to deliver more efficient, resilient, and cost-effective workload automation.
Key outcomes
- A phased roadmap to improve performance and reduce cost
- Safer change through simulation before implementation
- Prioritised fixes for overruns and recurring issues
- Clear visibility of processes and dependencies to pinpoint bottlenecks faster
What we provide
Batch discovery and mapping
Gain complete visibility with rapid process and dependency mapping across your workload environment. Understand how jobs interact and where bottlenecks occur.
Performance analysis
Identify the most problematic jobs, frequent overruns, and dependency latencies. We highlight inefficiencies that affect your business day and provide clear priorities for improvement.
Scenario simulation
Test and model proposed changes before implementation. Our simulations allow you to see the potential impact and optimisation opportunities without introducing risk.
Transformation roadmaps
Through phased and iterative transformation, we ensure your batch schedules evolve smoothly, maximising performance and minimising disruption.
How does it add value
Turn real operational data into clear, prioritised actions, and reduce recurring failures, shorten batch windows, and improve resilience without relying on guesswork or one-off tuning.
Why Ortom8?
Ortom8’s AI Optimisation service is designed by automation specialists who understand both the technology and the business impact of workloads. Our approach combines deep expertise with powerful tools, ensuring improvements are not just theoretical but practical, scalable, and aligned with your business goals.
FAQs
How does AI workload optimisation work?
AI optimisation analyses your workflows, dependencies, and job patterns to identify pinch points, redundant steps, dummy jobs, and areas where automation can be improved. It then helps redesign and optimise workloads so they run more efficiently, reliably, and with fewer delays.
Does AI workload optimisation help overcome data quality challenges for AI workload automation projects?
Yes, AI workload optimisation can help identify poor-quality, incomplete, or unreliable data earlier in the automation process, improving job performance, reducing failures, and helping AI workload automation projects run more accurately and efficiently.
How does machine learning improve job scheduling and resource allocation?
Machine learning plots trend and changes in the way schedules run and finds trends. It then identifies changes in the way the schedules run and identifies and expands bottlenecks.
Ready to transform your automation?
Whatever your starting point, Ortom8 has a solution that fits.
Get in touch to learn how Ortom8 can help your business work smarter, not harder.