Less time investigating incidents
Use ZResolv to bring incident context and resolution history together, assess likely causes and prepare the next action. Give consultants a starting point they can review and refine.
SAP Managed Services
SysAutonomy combines SAP expertise with AI to reduce repetitive support work and the staffing capacity it consumes. Our managed services approach focuses on lowering AMS costs while improving the business processes that depend on SAP.
We build ZResolv and ZForge into the way we deliver support and enhancements. AI assists with investigation and generation, with approved remediation as confidence grows. Consultants focus on exceptions, business decisions and changes that prevent the next incident.
AI in the delivery process
Repeated investigation, manual fixes and document preparation all add to the effort needed to run SAP. We target those activities so your support operation can handle demand with less manual intervention and a lower staffing requirement.
Use ZResolv to bring incident context and resolution history together, assess likely causes and prepare the next action. Give consultants a starting point they can review and refine.
Use ZForge to generate specifications, technical designs, code and unit test cases from agreed decisions. Reduce manual preparation across ABAP, RAP, CAP and CPI changes while retaining review and testing.
Review recurring incidents for opportunities to improve configuration, validation or the underlying process. Prioritize changes that remove avoidable demand from the support queue.
Keep resolution history and design decisions available to the team. Reduce the repeated research and handover effort that arise when essential context sits with one person.
Support with ZResolv
Begin with incident categories that consume substantial effort, such as failed IDocs, interrupted batch jobs or recurring integration errors. Our consultants use AI-assisted diagnosis and recommendations to investigate the issue and assess the next step.
As recommendation quality and measured savings build confidence, extend the approach to selected remediation tasks. The agent proposes the fix, an authorized person approves it, and the agent executes the approved action with a recorded outcome.
The objective is to reduce the human effort required per incident. That creates room to handle higher demand with the same team, redeploy capacity to improvements or reduce the staffing needed for the agreed support scope.
Development with ZForge
When routine support consumes the available team, useful improvements wait. We aim to release capacity for the changes that make business processes more reliable and reduce future support demand.
Our consultants use ZForge to turn agreed requirements into functional specifications, technical designs, code and unit test cases. AI handles much of the preparation; consultants resolve design questions, review the outputs and take changes through testing and release controls.
Prioritize the backlog by business value: removing a recurring interface failure, improving an exception check or simplifying a process that repeatedly generates tickets. Track delivery effort and whether the change reduces the problem it was intended to solve.
Business performance
Ticket volumes and resolution times tell only part of the story. We connect support priorities to the business processes affected, then agree the measures that show whether the service is helping.
Alongside support measures such as effort per ticket, repeat incidents and SLA breaches, track the business outcomes relevant to your landscape. Establish a baseline and review progress with your process owners.
Order processing
Track orders held by IDoc or interface failures, the time to release them and the effect on shipment deadlines.
Invoice processing
Monitor invoices delayed by posting or integration errors and the time needed to clear those exceptions.
Payroll and critical jobs
Measure completion against business deadlines and the frequency of failures that require urgent intervention.
Support productivity
Review manual effort per incident, repeat-ticket volume and capacity released, then track how those gains translate into lower AMS costs.
A measurable path to lower effort
Agree the scope around your incident mix, support workload and business priorities. Set a baseline for cost and effort, then use the evidence from delivery to guide automation and staffing decisions.
Review ticket volumes, handling effort, staffing and recurring failures. Identify the business processes affected and agree which operational and business KPIs to improve.
Start with a defined incident category. Measure recommendation quality, consultant effort and outcomes while agreeing approval responsibilities, access and escalation controls.
Extend approved remediation where results justify it. Review the capacity released and agree how to redeploy it or reduce the support requirement. Savings depend on translating reduced effort into changes in staffing or commercial scope.
Bring your support workload and the business KPIs you want to improve. We’ll show how ZResolv and ZForge support our delivery approach and discuss where AI can reduce manual effort, staffing demand and AMS costs.