For organisations whose reporting isn’t trusted yet

Fix the process behind your numbers. Then put AI to work.

We redesign how work flows, rebuild reporting on Microsoft Fabric and Power BI, and only then automate and apply AI, so decisions rest on numbers people trust.

Talk through your project See the case studies
CLEANDATA Microsoft Fabric OneLake Warehouse Semantic model Analytics &Reporting Agentic AI DISCONNECTED PROCESSES · INCONSISTENT DATANO SINGLE SOURCE OF TRUTH 01 UNDERSTAND &REDESIGN PROCESSES 02 UNIFYIN FABRIC 03 AUTOMATE& APPLY AI
Before AI

AI on untrusted data multiplies the problem.

  1. The numbers are argued about.Measures disagree, reports are rebuilt by hand, and meetings debate the figures instead of the decision.
  2. The process is the cause.Hand-offs, re-keying and rework create the errors that reporting later exposes.
  3. Fix it in order.Redesign the process, unify the data on Fabric and Power BI, then automate and apply AI with clear limits.
How we work

Start where it breaks: the process, the data or the hand-off.

Explore all services
Our methodology

Eight steps from requirement to a result that holds.

  1. 01

    Discover

    Agree the outcome, the decisions and the requirements.

  2. 02

    Current state

    Map how the work and data flow today, with evidence.

  3. 03

    Root causes

    Find what drives the delay, rework or disagreeing numbers.

  4. 04

    Approach

    Agree the target design, scope and measures of success.

  5. 05

    Build

    Build the new process, report, automation or agent.

  6. 06

    Optimise

    Test at real volumes; tune speed, cost and usability.

  7. 07

    Productionise

    Release with managed deployment, monitoring and support.

  8. 08

    Govern

    Set owners, access and controls so it keeps working.

Each engagement uses the steps it needs: a reporting rebuild may start at Current state, an AI agent always ends with Govern.

Interactive Power BI sample reports

See the reporting before you commit to it.

Scroll to turn the ring. Click the report in front to explore it.

Request Journey & Hand-off Analytics sample reportUnderstand & RedesignRequest Journey & Hand-off AnalyticsSales, Returns & Buying Patterns sample reportUnify in Fabric & Power BISales, Returns & Buying PatternsFabric Migration & Estate Operations sample reportUnify in Fabric & Power BIFabric Migration & Estate OperationsRetention & Discharge Operations sample reportCase StudiesRetention & Discharge OperationsQuality & Process Control sample reportCase StudiesQuality & Process ControlAutomation Operations sample reportAutomate & Apply AIAutomation OperationsFund Reporting & Reporting-Cycle Controls sample reportCase StudiesFund Reporting & Reporting-Cycle ControlsPower BI Estate Governance sample reportUnify in Fabric & Power BIPower BI Estate Governance
Explore this report All 20 reports
From the case studies

What changed in practice

Explore the case studies
Textile manufacturer · client-reported7 → 3 daysProduction lead timeWith a documented AUD 350,000 net saving over 18 months.Read the case Australian lender · client-reportedAUD 14k → 3kMonthly Fabric capacity costCapacity follows the workload instead of paying for peak all day.Read the case Consumer-products manufacturer150+ → 1Spreadsheets into one quality databaseInspection, traceability, assurance and analysis on one record.Read the case
How we keep learning

Research, checked before it informs delivery.

Specialist agents help us explore permitted sources and technical questions. People review the evidence before it informs a recommendation.

Read about our research approach
Research, checked and connected Technical questions and permitted references guide specialist agents. Evidence is checked before findings join our knowledge graph of sources and lessons. People review delivery options. Retained lessons feed further research. This describes an internal approach, not live activity. Lessons prompt new questions QuestionsSpecialist agentsEvidence check Delivery options Sources in scopePeople review Our knowledge graph Sources · findings · lessons
Our internal research approachSwipe to explore, or focus the diagram and use the arrow keys.
Technical questions and permitted references guide specialist agents. Evidence is checked before findings join the knowledge graph. People review delivery options. Retained lessons prompt further research.
Manish Sharma · Founder & Principal Architect

Where does work get stuck, or the numbers stop adding up?

Tell us. You work directly with the architect who designs the solution. We can start with a short review of where measures disagree and where the process breaks, then agree the order of work before any AI is scoped.

Talk through your projectSee the case studies