Migrate & Modernise

Migrate with confidence and modernise for what comes next

Customer problems we solve

Organisations running on premises or hosted infrastructure face rising costs with no flexibility. Every month of delay compounds technical debt and consumes budget that should go to innovation. Legacy systems slow progress. Traditional security models cannot defend against modern threats. And organisations cannot run AI workloads on legacy infrastructure, which makes migration the prerequisite to every AI initiative the business wants to pursue. Previous attempts may have failed because a lift and shift approach transferred problems to the cloud without transformation. For analytics environments, legacy reporting tools, ageing data warehouses, fragmented semantic models and customised pipelines create complexity that makes migration feel slow, expensive and uncertain. Agile Insights reduces this uncertainty through expert-led planning combined with AI-assisted analysis, agentic automation and repeatable delivery methods.

Your migration journey

Agile Insights approaches migration as a structured programme of assessment, modernisation and transition. For infrastructure, the Agile Migration Factory uses agentic SDLC capabilities to power an AI-driven factory model. Intelligent agents handle discovery, infrastructure as code generation, pipeline creation, validation and self-healing operations, with human in the loop governance at every critical decision point. For analytics and data platform migrations, the objective is a better architecture, stronger governance and a more scalable operating model.

01. AI enabled assessment and migration strategy

Agile Insights begins by assessing the existing environment across infrastructure workloads, reports, semantic models, pipelines, datasets, warehouse assets, dependencies and usage patterns. For infrastructure, this includes automated portfolio discovery with dependency mapping, comprehensive TCO and FinOps modelling against rightsized Azure, security posture evaluation and AI readiness analysis. The assessment produces a prioritised migration roadmap and business case with clear executive decision support. For analytics, this stage establishes migration scope, identifies complexity hotspots and defines the right path based on business priorities. Proprietary tools, AI-assisted analysis and proven assessment frameworks help accelerate discovery, design and planning.

02. Migration delivery and platform modernisation

Once the target state is defined, Agile Insights delivers the migration using repeatable frameworks, automation accelerators and AI-assisted methods. For infrastructure, the Agile Migration Factory deploys the Agile SDLC agentic engine integrated with GitHub Enterprise. AI agents generate Bicep, Terraform and YAML from requirements rather than hand crafting infrastructure as code. Workloads move in structured waves with automated validation. Azure Monitor connects to agentic workflows for propose and fix operations from day one. For analytics, this includes migration of Power BI content, reporting assets, semantic models, data pipelines and warehouse workloads into Fabric and related Azure services. Proprietary migration patterns and experience-led delivery methods reduce effort, improve consistency and modernise as part of the move.

03. Validation, transition and optimisation

Migration is only complete when the new environment is trusted, adopted and performing as expected. For infrastructure, the factory scales through subsequent waves of five to fifteen workloads each. Infrastructure as code catalogues are hardened, self-healing operations are extended, team roles and accountability are formalised through RACI and runbooks and a factory playbook is handed over so the organisation owns the platform. Agile Insights also validates migrated reports and data assets, supports business transition and refines the platform for performance, governance and maintainability. For analytics, this means embedding the semantic model design, governance controls and operating practices needed for long term success.

What you get

For infrastructure: a working Agile Migration Factory that becomes a permanent organisational asset, AI-generated infrastructure as code and pipelines, self-healing operations from day one and a modern Azure foundation ready for data, analytics and AI. Across all migrations: a structured path with lower delivery risk, faster assessment through AI enabled analysis, reduced manual effort through proprietary frameworks and accelerators, and improved target architecture, governance and performance. For analytics: a modern data platform designed for future reporting, self-service and AI.

Enablement and Training

Agile Insights supports migration success through practical enablement for administrators, developers, analysts and business stakeholders. This includes transition support, governance guidance, semantic model and reporting standards and targeted training to help internal teams operate the new platform with confidence. For infrastructure, enablement includes factory runbook documentation, team role definition across platform, application, security and FinOps and hands-on experience with the agentic migration factory model.

Why Agile Insights

Agile Insights has developed proprietary IP including the Agile Migration Factory, powered by the Agile SDLC agentic platform and combining deep Azure and GitHub Enterprise expertise with practical migration delivery across infrastructure, reporting, analytics and data estates. For infrastructure, agents handle discovery, infrastructure as code generation, pipeline creation, validation and self healing operations, turning migration from a manual project into a repeatable factory. For analytics, reusable frameworks and AI-enabled delivery methods allow organisations to move with greater speed and confidence while improving target state quality.