Move from Reporting What Happened to Recommending What to Do Next.
Your enterprise data holds patterns, anomalies and opportunities that static reports will never surface. We build the pipelines, models and decision-support agents that turn your historical data into forward-looking intelligence.
Intelligence That Acts — Not Just Reports That Inform
Dashboards tell you what happened. Predictive models tell you what will happen. Decision-support agents tell you what to do about it. We build all three — starting from your existing data sources.
Our data intelligence practice covers the full stack: clean pipelines on Microsoft Fabric and your data infrastructure, predictive models trained on your historical data, anomaly detection across financial and operational flows, and agent-driven recommendations that surface the right action to the right person.
Executive Dashboards
Real-time performance tracking for leadership — financial, operational and strategic KPIs in one governed view.
Predictive Analytics
Cash flow forecasting, demand prediction and risk modelling trained on your historical data — not industry averages.
Anomaly Detection
Automated flagging of unusual patterns across financial and operational flows — before they become material issues.
Decision-Support Agents
Agents that recommend the next action — not just surface the data — so your team spends time on judgement, not investigation.
What Changes When Agents Handle This Work
From reactive to proactive
Anomalies, shortfalls and opportunities are surfaced before they become problems — giving your team time to act rather than respond.
Forecasts built on your data
Predictive models trained on your historical patterns — not industry benchmarks — deliver forecasts that reflect your actual business dynamics.
Leadership sees the signal, not the noise
Executive dashboards surface the metrics that matter, with drill-down to the transaction level — without requiring an analyst to prepare each view.
Recommendations, not just reports
Decision-support agents go one step further — ‘here is the anomaly, here is the likely cause, here is the recommended action’ — reducing cognitive load.
Connects your entire data landscape
Pipelines draw from your ERP, CRM, operational systems and external data sources — a unified view, not siloed reports from each system.
Built on enterprise-grade infrastructure
Microsoft Fabric for data lakehouse architecture and pipelines, Azure AI Foundry for model services — platforms your IT team can govern.
What We Deliver
Data engineering and pipelines
Clean, governed pipelines from source systems to analytics layer — on Microsoft Fabric, Azure or your existing data infrastructure.
Executive performance dashboards
Real-time operational and financial dashboards designed for leadership consumption — with drill-down to transaction level.
Cash flow forecasting
Predictive cash flow models trained on your AR/AP data — surfacing funding requirements and surplus positions weeks in advance.
Demand and inventory prediction
Forecasting models for inventory optimisation and demand planning — integrated with your ERP purchasing and supply chain data.
Financial anomaly detection
Automated flagging of unusual journal entries, duplicate payments, variance spikes and outlier transactions — before period end.
Operational exception detection
Monitoring across fulfilment, procurement and service delivery data — flagging performance deviations in real time.
Decision-support agent layer
Agents that analyse, synthesise and recommend — turning detected anomalies or forecast deviations into actionable guidance.
Microsoft Fabric architecture
Data lakehouse design, OneLake configuration, Dataflow pipelines and Fabric workspace governance — delivered and documented.
How We Deliver
Data Landscape
We audit your data sources, quality, granularity and governance posture — identifying what is usable now and what needs to be fixed.
Pipeline Build
Clean, governed pipelines from your ERP, CRM and operational systems into a unified data layer — on Fabric or your existing infrastructure.
Model Development
Predictive and anomaly-detection models trained on your historical data — with clear documentation of assumptions and limitations.
Dashboard & Agent Layer
Dashboards for your teams and decision-support agents that surface recommendations — not just data.
Monitor & Retrain
Ongoing model performance tracking, drift detection and retraining — so accuracy improves as your data grows.
From Data to Decisions — Not Just Data to Dashboards
Decision-support agents, not just BI tools
We go beyond dashboards. Our decision-support agents surface the anomaly, explain the likely cause and recommend the action — reducing time from insight to response.
Models trained on your data
Predictive models are trained on your historical patterns, not industry benchmarks. Forecasts reflect your business dynamics — not someone else’s average.
Honest about data quality
We tell you what your data can and cannot support at the start. No false promises about accuracy from poor-quality inputs.
Enterprise infrastructure, not experimental tools
Microsoft Fabric, Azure AI Foundry and your existing data stack — production-grade platforms that your IT and governance teams can manage.
Proactive Intelligence
Problems surfaced before they become material. Opportunities identified before they close. Recommendations at the point of decision.
Questions We Hear Every Time
QOur data quality is poor. Do we need to fix that before starting?▾
Not entirely — but we will be honest about what your data can and cannot support at the start. We identify data quality issues as part of the landscape audit and can address them as part of the engagement.
QDo we need Microsoft Fabric or Azure, or can you work with our existing data platform?▾
We work with your existing infrastructure. Microsoft Fabric and Azure AI Foundry are our preferred platforms for new data architectures, but we have experience across Snowflake, Databricks, Redshift and on-premise data warehouses.
QHow do decision-support agents differ from a standard dashboard?▾
A dashboard shows you a number. A decision-support agent shows you the number, explains the likely cause, compares it to your historical pattern and suggests a specific action — reducing the time from ‘I see the problem’ to ‘I know what to do about it’.
QHow quickly can we see early results?▾
An initial executive dashboard over your existing ERP data can typically be live within weeks. Predictive models require more historical data and take longer to validate — we will set clear expectations on timeline by use case in the discovery phase.
What Decision Would Change If You Had 30-Day Visibility Instead of Last Month’s Report?
Start with that question. We will show you what is achievable against your current data landscape — and what the path from static reporting to forward-looking intelligence looks like in your environment.
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