Indium Recognized as a Product Challenger in ISG-One’s Generative AI & Agentic AI Services Assessment, 2026
Bringing Reliability, Accuracy, and Autonomy to Modern Enterprises
ISG Research recognizes Indium’s capabilities in leveraging agentic platforms to automate system understanding and support the re-architecting of enterprise environments with scalable, governed, and increasingly autonomous AI solutions.
Indium takes pride in serving its customer build a roadmap for scalable AI agents by mapping agent workflows, enabling agents to execute tasks across applications, and generating signals that continuously refine agent behavior all while enforcing appropriate governance guardrails.
Indium’s Shift Towards Autonomous Enterprises
Indium introduced The Lifter, an agentic platform designed to help enterprises move toward more autonomous, AI-ready environments.
The Lifter helps enterprises:
1. Understand legacy estates before modernization by uncovering business logic, dependencies, and context embedded across complex systems.
2. Modernize and migrate data with context intact, helping enterprises preserve the business meaning and relationships that can otherwise be lost during transformation.
3. Test and optimize systems before deployment, enabling enterprises to identify gaps and validate system behavior before they impact business operations.
Beyond modernization, The Lifter enables agentic use cases across enterprise workflows—from managing approval cycles and supporting patient-care operations to building catalog intelligence that improves product enrichment.
The result? AI that moves towards context-aware decisions and autonomous execution with greater reliability, governance, and business impact.
Discover how Indium is helping enterprises build more autonomous, efficient, and resilient operations with agentic AI—transforming enterprise architecture while maintaining the privacy, security, and governance required for responsible AI adoption
Real Stories,
Real Impact
The Indium Advantage
Modernization slows when legacy systems are disconnected, poorly documented, and difficult to understand. Legacy Lifter automates the analysis of large and undocumented codebases, mapping dependencies and surfacing the business context embedded within legacy systems.
Impact: shortened assessment cycles, uncovered hidden risks early, and reduced effort required to understand complex legacy environments.
Enterprise migrations can compromise the business meaning and relationships embedded across fragmented data environments. Data Lifter analyses legacy schemas, data dependencies, and relationships across enterprise environments to help preserve semantic integrity during migration.
Impact: up to 40% reduction in manual migration effort for accelerated migration.
Meeting predefined quality assurance metrics does not always guarantee that a modernized system will behave as expected in production. Test Lifter uses AI-driven test generation, impact-based regression testing, and self-healing capabilities to validate modernization outcomes against real system behavior.
Impact: up to 70% reduction in test cycles and increased confidence in modernization outcomes.
When applications are many and disintegrated, every system migration and operational handoff creates the risk of losing critical context. AMS Lifter addresses this by building a governed context graph across the application estate, connecting system context with incident history and making that knowledge available throughout the incident lifecycle.
Impact: 25-40% MTTR improvement and reduced repeated investigation.
