What we do
One Microsoft foundation for data, analytics, copilots and agents.
We stand up new data and AI platforms, modernize legacy estates, and build governed agentic capability on Azure, Fabric and Foundry. The work starts from a business question, shows something working quickly, then builds the production foundation around whatever holds up.
Where clients start
Two starting points, one production-ready foundation.
The entry point differs. The destination does not, which is a governed Microsoft platform that belongs to you and can carry more than the use case that justified it.
Build new
You have a use case and no platform under it
A question the business needs answered, a process worth automating, or an assistant that has to be grounded in something more trustworthy than a document library. We agree the outcome, build a working proof of value, and establish the Fabric and Foundry foundation needed to put it into production.
Modernize
You have valuable work trapped in a platform that cannot continue
Data, reports, definitions and workflow logic sitting in an environment that is expensive, unsupported, or understood by one person. We recover what the environment actually does, keep what still matters, and move it onto the Microsoft-native stack.
The technical scope
What we own, in the order it usually gets built.
We stay inside the Microsoft data and AI platform layer. For net-new landing zones, broad infrastructure programmes and general application development, we bring in a specialist rather than presenting as a generalist.
Platform
Microsoft data and AI foundation
Fabric capacity and workspace architecture, OneLake and the data structures over it, ingestion and transformation patterns, semantic models and Power BI, Foundry projects and grounding, and the governance, lineage, identity, security and cost controls that make it a production system rather than a deployment.
Modernization
Legacy estates and the logic inside them
Cognos, Tableau, Qlik, Crystal Reports and SSRS. Informatica, Oracle and SQL Server. Custom applications whose real function is data, reporting or workflow. Business-logic recovery, parity validation where it is required, and modernization where it earns its place.
Agents
Copilots and agentic systems
Agents grounded in governed data and certified semantic models rather than in a pile of documents. Processes that combine deterministic tools with model reasoning, with identity, citation, fallback and human-routing patterns, plus the monitoring to see what they are actually doing in production.
Continuous
Operation and expansion
Running the platform under ManagedIQ. Governance and security maintenance, performance and cost optimisation, and steady expansion into new sources, use cases, agents, teams and business units as the organisation finds more it wants to ask.
When you are modernizing
Wherever you are starting from.
We are not a Cognos shop or a Tableau shop. We are good at the translation itself, which means the system you are leaving matters less than most vendors will tell you.
Reporting platforms
Cognos, Tableau, Crystal Reports, SSRS
Mature reporting estates with real logic buried in them. The hard part is never the charts. It is the calculations nobody has written down.
Custom applications
The app nobody maintains
Usually built for a good reason a decade ago, usually by people who have moved on. Often it is a data warehouse and a set of reports wearing an application costume.
Spreadsheet estates
The quarterly workbook
A file that four people maintain by hand, that the business genuinely depends on, and that nobody is willing to be the one to break.
Existing warehouses
Oracle, SQL Server, and older cloud builds
Infrastructure that met the demands of the last decade and cannot meet the next one. Moving it is less risky than leaving it.
The migration method
Modernization is a translation problem.
A legacy estate holds more than code and data. It holds years of definitions, exceptions and workarounds that may not exist in any document. We read the source, the data and the outputs together, then use AI to accelerate the translation while senior practitioners confirm what has to stay true.
- 01
Read the estate
Sources, logic, outputs, reports and live behaviour, analysed together. We find where the documentation and the running system disagree, and there are always places.
Weeks, not quarters
- 02
Recover what matters
The business rules, definitions and dependencies worth keeping, separated from the accidents of an old platform that nobody would choose to rebuild.
Verified, inferred, unconfirmed
- 03
Rebuild and validate
Artifacts generated and translated, then tested against real outputs and intended behaviour. Parity first where parity is required, so nobody has to relearn their job on day one.
One-to-one where it counts
- 04
Keep going
Workloads move in manageable groups while ManagedIQ keeps improving the platform underneath them. The estate gets better because it is being used.
Ongoing
Where should the platform create value first?
Tell us the question the business cannot answer, or the system that has to move. We will tell you what we think it takes.