Why I Built This
Every CFO I've worked with had the same problem.
After 16 years designing analytical platforms for mid-market companies across the UK and Canada, I kept seeing the same gap: finance teams drowning in ERP reports that told them what happened last month, while the questions that actually mattered — cash in 90 days, which customers will default, are we heading for a covenant breach — had no answer.
Teaching macroeconomics and computational macro-strategy at Dawson College sharpened my conviction that the tools to answer these questions already exist — they just haven't been assembled for the mid-market CFO. I built C-Suite Intelligence to close that gap.
The architecture selects the right tool for each layer of the problem — dlt for schema-resilient ingestion, DuckDB for cost-efficient transformation, dbt for governed Gold models, XGBoost and Chronos for prediction — and introduces Microsoft Fabric or ADF only when the economics justify it. The result is enterprise-grade decision intelligence at infrastructure cost.
Background
Built on 16 years of enterprise delivery.
Architecture-First
Every engagement starts with structured discovery workshops with the CFO, CRO, and DPO — before a single line of code is written. The architecture is co-designed with the client.
End-to-End Delivery
From ingestion (Salesforce, SAP, ERP REST APIs) through Bronze/Silver/Gold medallion layers to governed Power BI semantic models — with RLS, OLS, and full lineage throughout.
Predictive Modelling
XGBoost, Random Forest, and Chronos time-series forecasting with SHAP explainability — translating ML outputs into narratives executives can present to their board.
Governance & Compliance
Microsoft Purview implementations covering GDPR right-to-erasure, DLP, sensitivity labels, and ICO-ready audit trails. Clients have passed external audits with zero findings.
Macro Intelligence
PhD-level grounding in economics applied to real business problems — BoC rate trajectories, yield curve signals, and TSX sector rotation translated into capital allocation decisions.
Academic Rigour
Professor of Macroeconomics and Computational Macro-Strategy at Dawson College, Montréal. Every model delivered to clients is grounded in the same rigour taught in the classroom.
How We Answer the Questions
The right tool for each layer. No over-engineering.
We select the architecture based on what the question requires — not on vendor relationships. ADF and Microsoft Fabric are introduced only when the volume or governance requirements justify the cost.
ADF replaces dlt · Microsoft Fabric replaces ADLS + DuckDB + Azure SQL — when volume or governance economics justify it
“What will our cash position be in 90 days?”
AP/AR transactions ingested via dlt into Bronze, cleaned in DuckDB Silver, modelled in dbt Gold. Chronos runs probabilistic P10/P50/P90 forecasts on the Gold layer. Output surfaced in Power BI in under 60 seconds.
“Are we heading toward a covenant breach?”
DSCR computed from Gold financial models updated on each ERP ingestion cycle. Stress-tested at +100 and +200bps using scenario parameters stored in dbt. Alert threshold breaches trigger Power Automate notifications before the close.
“Which customers will default before they miss a payment?”
AR aging, payment history, and sector macro signals joined in the Gold layer. XGBoost ensemble scores every active account weekly with SHAP waterfall explanations surfaced directly in the account-manager view.
“Where is macro risk entering our cost structure?”
BoC rate trajectory, CPI/IPPI compression, and TSX sector rotation ingested from public APIs alongside your ERP data. dbt models link external signals to your margin and covenant metrics — no manual Excel overlays.
Let's talk about your data.
A 45-minute discovery call. No slides. We connect to your data and show you three insights your team has never seen before.