Avolution provides an AI‑powered enterprise architecture platform that automatically discovers and maps applications, services, and cloud resources across large organizations. The system uses machine‑learning analytics to surface cost‑optimization opportunities, technical debt, and risk hotspots, delivering interactive visualizations and scenario modeling for data‑driven IT strategy decisions.
Funding
Funding not disclosed
Founders
Product
Problem
Enterprises face rapid growth in applications and cloud adoption, leading to increasingly complex IT landscapes that are difficult to monitor, analyze, and align with business objectives. The volume of technical and financial data generated makes it hard for architects to identify bottlenecks, technical debt, and cost inefficiencies.
Solution
Avolution offers an enterprise architecture platform that applies AI and machine learning to ingest large datasets from applications, cloud services, and infrastructure. The system automatically maps relationships, detects patterns, and surfaces actionable insights such as migration opportunities, cost optimization, and risk hotspots. By visualizing the architecture’s structure and connections, the platform helps architects monitor growth, assess technical debt, and align technology decisions with strategic goals. Recommendations are presented in an intuitive dashboard, enabling faster, data‑driven decision‑making across the organization.
Target Audience
Primary users are enterprise architects, IT strategy teams, and technology governance groups within large organizations undergoing digital transformation and cloud migration.
Features
- AI‑driven automated discovery and mapping of applications, services, and cloud resources across the enterprise
- Machine‑learning analytics that identify trends, bottlenecks, and technical debt from heterogeneous data sources
- Cost‑optimization insights highlighting under‑utilized assets and migration opportunities
- Interactive visualizations of architecture layers, dependencies, and business alignment
- Scenario modeling tools to evaluate the impact of architectural changes before implementation
- Integration with existing IT management and governance tools for seamless data ingestion