DTS Global Extends Alpaca AI From Enterprise Asset Management Into Plant Turnarounds

DTS Global markets itself as an information integrator certified across major ERP systems, including SAP and Oracle. The company’s Alpaca assistant embeds large language models inside enterprise asset management systems, adding AI-driven analysis, translation, and workflow support without pulling users into a separate application. DTS reports deploying six AI integrations within one fleet-wide asset management system, spanning functions such as one-shot translation, failure coding, and conversational risk assessments, and says the deployment produced more than 84,000 interactions. The company frames this work around the daily demands of teams responsible for running and maintaining plants and mobile equipment fleets.

Turnaround Workspace: Consolidating Plant Turnarounds Into One Live Dashboard

Turnaround Workspace applies that same live-data approach to plant shutdowns. The dashboard consolidates readiness tracking, an interactive unit map, and P&ID drawings into a single view that reads directly from a plant’s source systems. DTS states the tool converts drawings into structured, living data with no CAD dependency, and the same interface also holds work orders, a lookahead schedule, and craft progress tracking.

The dashboard’s core mechanism rolls up thousands of individual asset tags into one readiness figure. DTS reports one deployment that consolidated 8,594 tags this way and projected a finish date directly from the actual closure rate. A punch burndown function gates turnover, meaning closeout activity must clear before a unit returns to operations.

Alpaca AI is embedded on every screen of the workspace and answers questions from the live database at the moment they are asked. DTS states that every figure the assistant quotes is traceable back to its source records. The product’s origin traces to a specific case, the world’s first commercial-scale ionic-liquids alkylation unit, a plant DTS describes as having no prior turnaround to copy, which meant readiness calls had to be built directly from data since no earlier project existed as a template.

SAP customers running Plant Maintenance or enterprise asset management modules often coordinate turnarounds through separate planning tools or manual spreadsheets, since shutdown scheduling sits outside standard core functionality. A dashboard that reconciles tag-level status automatically addresses a workload that otherwise falls to planners working across multiple systems by hand. The emphasis on traceable AI answers also reflects a broader pattern across ERP-adjacent tools, where auditability has become a baseline expectation for AI used in safety-critical operational settings.

eMESA Live and EPlus 4: The Workflow and Data Layer Behind the Platform

DTS describes two components forming the layer beneath its turnaround product. eMESA Live is a role-based workflow system designed for the complex process requirements of asset-intensive industries, giving different users tailored views of the same underlying operations.

EPlus 4 is described as a patent-pending data engine built for flexibility, power, and security, with the capacity to design applications in real time.

Role-based workflow interfaces of this kind resemble a pattern familiar to SAP customers through Fiori’s role-based app design, which similarly tailors screens to specific job functions across EAM and Plant Maintenance landscapes. A data engine built for real-time application design also fits a broader industry shift toward low-code and extension platforms, tools organizations use to adapt core ERP functionality without altering the underlying system. DTS does not draw either comparison itself; the parallels reflect patterns common across the broader SAP ecosystem.

What This Means for SAPinsiders

• AI answers now traceable to live data. SAP asset and turnaround teams gain readiness figures and schedule projections they can verify against source records directly. That traceability reduces the manual double-checking that typically accompanies AI-generated reporting during shutdown planning.
• Multi-ERP certification broadens buyer fit. Certification across SAP, Oracle, and other ERPs means prospects can evaluate DTS regardless of their core system. SAP-specific teams should still confirm integration depth with their own PM or EAM configuration before committing.
• Six AI integrations signal scaling AI use. Over 84,000 logged interactions point to AI usage moving beyond pilot scale within asset management workflows. Organizations adopting a similar layer will need governance processes covering data quality, change control, and user training as volume grows.