Three Use Cases
- Application Retirement
- M&A Data Preservation
- AI Enablement
Challenges This Addresses
- Legacy systems running on unpatched, unsupported software exposing your organization to ransomware and data exfiltration attacks
- Cloud migrations leaving decades of historical data stranded in legacy ERP, mainframes, and custom applications — inaccessible after decommission
- M&A data complexity: inheriting unfamiliar systems and data models with no institutional knowledge, under tight contractual timelines
- Dark data from acquisitions that is unclassified, ungoverned, and unusable — blocking AI readiness initiatives
- End-users demanding full access to legacy data with no practical path to satisfying that demand after application shutdown
What You’ll Learn
- Why legacy system decommissioning is now a CEO and CISO-level security mandate, with real 2025 CVE examples
- How the Application Knowledge Graph enables natural-language queries against complex enterprise schemas (Oracle EBS, SAP ECC, PeopleSoft)
- The Solix Connect → Migrate → Enable AI workflow for M&A data ingestion and governed access
- Architecture of the Preservation Zone: data validation, metadata preservation, intelligent classification, and retention management
- How preserved historical data becomes training ground for enterprise-specific LLMs, SLMs, and AI digital workers
- Data sovereignty and international AI policy implications — EU AI Act, India’s 2026 AI Governance Guidelines, U.S. state-level patchwork
- How the evolution from EBR keyword search (2020) to NL2SQL Knowledge Graph access (2026) eliminates end-user resistance to archiving
- Key market trends from Gartner’s June 2025 Market Guide for Data Archiving Solutions
Why This Matters for Enterprise Architects
Enterprise data preservation has evolved from a cost-reduction exercise into a strategic imperative. Preserved data is no longer a burden to be maintained at minimum cost — it is fuel for intelligent analysis, model development, and competitive differentiation. Organizations that approach data preservation with an AI-first perspective, treating every preserved data set as a potential input to future AI models and digital workers, will be far better positioned to lead in the AI era.
About the Author:
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Mark Lee is Chief Product Officer at Solix Technologies, where he leads product strategy across all Solix products, including Solix EAI – Enterprise Edition.
About Solix Technologies
Solix Technologies is a leading provider of enterprise data management, AI, and cloud data solutions trusted by Fortune 2000 companies worldwide. The Solix Common Data Platform (CDP) delivers cloud-native solutions for enterprise archiving, data lakes, data governance, sensitive data discovery, and Enterprise AI — all on a single open multi-cloud architecture.
Last Reviewed: April 2026
