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TransisTOR Powers Data-to-AI Acceleration with Oracle AIDP
TransisTOR is LTIMindtree’s advanced transformation engine for Oracle AI Data Platform (AIDP). It enables data modernization by moving fragmented on-premises and cloud environments into AIDP with precision and reliability.
TransisTOR transitions data structures, metadata, pipelines, ingestion flows, and governance mechanisms into native AIDP services. This protects your investments in data engineering and governance tools while preparing operations for analytics and AI from day one.
With industry-standard KPIs, accelerators, and agentic AI, data migration to the cloud becomes secure, efficient, and risk-free, helping you move from data chaos to AI confidence.
Accelerated Time-to-Value: Automated discovery of data assets and migration processes shortens project timelines, allowing organizations to transition from migration to operational AI in weeks instead of quarters. This reduces costs associated with long-term projects and speeds up revenue realization.
Investment Protection & Cost Control:Reuse existing logic and pipelines, adopt open formats like SQL and Parquet, and minimize integration costs by reducing re-engineering expenses and avoiding vendor lock-in (reliance on proprietary platforms). This maximizes ROI and ensures flexibility for future development and modernization.
Simplified Experience, Lower Risk:Guided workflows and automated validation reduce manual errors, cut down troubleshooting, and keep teams focused on strategic goals like compliance reporting, faster financial closes, and supply chain optimization.
Immediate AI-Driven Impact: Agentic AI predicts demand and risks, suggests actions for operations and finance, and shares the story of performance trends in ways teams can act on immediately to improve decisions.
TransisTOR simplifies and accelerates data modernization by moving fragmented data platforms to Oracle’s AIDP. It automates conversion, preserves governance, and ensures your environment is operationally ready for AI-driven value creation.
Preserve data structures, ingestion, transformation pipelines, and governance for quality, lineage, and security. This allows AI analytics and decision-making to begin immediately, speeding up reporting and insights.
Automated conversion reduces manual effort, such as schema rewrites and job recording. It accelerates modernization timelines for data and analytics workloads, and leverages existing logic and assets like SQL transformations, business rules, and policies. This approach cuts re-engineering costs and limits the total cost of ownership (TCO).
An intuitive TransisTOR interface and step-by-step workflows help teams focus on business outcomes such as faster reporting, compliant KPIs, and automated decisions, instead of migration mechanics like field mappings, pipeline rewrites, or policy reconfiguration. This shortens the learning curve and boosts the adoption of AI-ready data.
Standardized KPIs, industry accelerators (finance close, supply-chain planning, CX personalization), and Agentic AI deliver actionable insights tied to operational and financial metrics. This ensures data estate modernization results in measurable business outcomes.
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