Track record · Workforce Intelligence
Rebuilding the foundations of an enterprise platform
An architectural review uncovered serious data, architecture and product-readiness issues. The turnaround rebuilt both applications, the underlying data platform and the AI capability, while migrating the wider cloud estate between Azure tenants. Delivered by TechGuidr founder Dan Warrener in a previous technology leadership role.
The situation
Workforce Intelligence, a UK technology-enabled learning and wellbeing business, was developing an employee performance and wellbeing application, an enterprise intelligence platform, complex scoring and diagnostic capability, organisation-level analytics and AI-assisted briefings for leadership teams.
The estate had grown across multiple clouds, services and technology generations, and the product appeared substantially further advanced than the technology underneath it really was.
What the review found
The problem ran deeper than ordinary technical debt. The review found material gaps between the apparent product capability and the underlying data architecture, including executive dashboards disconnected from live production data and scoring pipelines that did not implement the authoritative calculation methodology.
Around that sat a fragmented multi-cloud architecture, brittle integrations, inconsistent engineering and deployment practice, and substantial accumulated debt. A report alone was not going to fix any of it.
The rebuild
Dan led the redesign and did the substantial part of the implementation personally: hands-on enough to know exactly what was happening, rather than managing the transformation from a slide deck.
- Both principal applications rebuilt from the ground up
- Core data platform re-architected on an Azure Databricks Medallion lakehouse
- A complex 227-question scoring methodology translated into verified analytical pipelines
- A structured dimensional model: fifteen dimensions, eight fact tables
- Executive analytics connected to live data
- Context-aware AI Coach grounded in the aggregated analytics layer
- Identity, deployment and environment controls strengthened
- Legacy service sprawl consolidated and removed
The tenant-to-tenant migration
The original tenant had never been set up coherently, and it sat in the wrong Azure region for the business. Rather than patch around it, Dan carried out a full tenant-to-tenant migration: identities and Entra configuration, subscriptions, app registrations, databases, storage, DNS and domains, and the deployment pipelines, consolidated into a correctly designed tenant in the right region.
Continuity was maintained with a planned, brief cutover. Any CIO who has lived through a tenant migration knows how technically and politically awkward that is to do without breaking the business.
The AI was the smallest part.
The AI Coach answers executive questions in the context of whatever the leader is looking at, grounded in curated, aggregated, mathematically validated enterprise data rather than raw employee records.
The model was the easy bit. The data foundations, verified calculations, privacy boundaries and user experience were the work.
What changed
The platform moved from fragmented, partially disconnected technology to a coherent enterprise architecture connecting transactional applications, verified analytical calculations, executive intelligence and applied AI, with both rebuilt applications in production. Dashboard queries that had taken four to five seconds returned in under 600 milliseconds once the unnecessary middleware was removed.
Programme green on the dashboard, red everywhere else?
This is what looking underneath the surface finds, and what fixing it properly looks like.