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:
-
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, Inc. (Santa Clara, CA) is a leading Data + AI company helping Fortune 2000 enterprises transform enterprise data into trusted AI-powered business outcomes. The Solix Common Data Platform (CDP), Enterprise Content Services (ECS), and Enterprise Data Governance (EDG) provide a trusted foundation to unify, govern, secure, and activate enterprise data for AI. Solix Enterprise AI (EAI), a fourth-generation AI-native data platform, combines enterprise data warehousing, semantic intelligence, natural language interaction, and autonomous AI agents. With capabilities such as Data Sense and Data Ask, organizations can interact with enterprise data in plain language, build AI-powered applications, automate business processes, and deploy intelligent agents on trusted enterprise knowledge. Supporting multi-cloud, hybrid, and sovereign AI deployments, Solix enables organizations to securely manage and activate data wherever it resides.
