Application Inventory
Application Inventory is a unified platform that consolidates fragmented application data from multiple sources—such as ServiceNow, Dynatrace, CMDBs, and discovery tools—into a single, trusted view. It standardizes this information into a common model, maps dependencies, and provides a foundation for modernization planning, Inventory governance, and topology insights.
Before modernizing, organizations must understand their current application landscape. Application Inventory provides a clean, accurate, and enriched baseline view of all applications, enabling data-driven decisions, risk assessment, and prioritized modernization roadmaps.
It connects to a variety of enterprise tools—such as CMDBs, observability platforms, and discovery solutions—and automatically consolidates, standardizes, and enriches data, reducing manual reconciliation efforts.
Yes. Application Inventory supports Bring Your Own Data in the Onboarding phase. It helps the user by providing tools that enable to convert your data into a consumable format.
- Application Inventory: Centralized visibility and governance for your application landscape.
- Topology Visualization: End-to-end mapping of application, infrastructure, and data dependencies.
- Application Modernization Intelligence: AI-powered insights for prioritizing and executing modernization.
By combining Inventory data, dependency mapping, and, KPIs defined to identify modernization candidates, assesses technical debt, evaluates risk, and aligns opportunities with business priorities.
Stakeholders across the organization— Solution Architects, Chief Architects, Application Owner. Site Reliability Engineers, IT Ops Admin, GTM (pre sales), CIOs, Inventory managers,—gain tailored views and insights to make informed decisions.
The three pillars— Application Inventory, Topology Visualization, and Modernization Intelligence—feed into an Actionable Priority Roadmap, which outlines what to modernize, when, and how, based on cost, risk, and business impact.
Yes. It provides recommendations for cloud readiness as well as optimization of existing on-prem environments, ensuring modernization strategies are balanced and cost-effective.
Data from multiple sources is reconciled and normalized into a Common Data Model, eliminating inconsistencies and creating a reliable baseline for assessments and decisions.
Organizations typically start seeing actionable insights within weeks of onboarding, as data ingestion, normalization, and dependency mapping are automated and rapid.