Enterprise Energy Procurement & Intelligence Platform
From a legacy SQL/Power BI tool to a serverless, AWS-driven forecasting and arbitrage intelligence engine.
1. Starting Point: A Fragile Legacy Stack
The organisation originally relied on:
- A single SQL database living on ageing on-prem hardware.
- Power BI dashboards stitched together manually.
- Slow refresh cycles, limited modelling, and no ability to forecast or simulate market exposure.
Energy traders, procurement teams, and executives were forced to make multimillion-dollar decisions using rigid tools that couldn’t handle:
- Spot price volatility
- Network loss-factor behaviour
- Contract exposure
- Probability scenarios for risk and arbitrage
The system was functional but fundamentally capped. It required a full rebuild if it was going to support modern energy procurement.
2. Transformation: Rebuilding the Entire Stack in the Cloud
The project rebuilt the legacy system into a fully cloud-native, serverless architecture powered by AWS.
Key achievements:
Serverless, infinitely scalable data layer
- Migrated all SQL workloads into AWS-managed services.
- Implemented event-driven ingestion for NEM data, network tariffs, contract updates, and market prices.
- Created multi-year storage for market history, enabling long-term modelling without performance degradation.
Advanced forecasting & probabilistic modelling
The platform can now simulate:
- Forward spot price curves
- Network behaviour under different seasonal and demand conditions
- Contract vs spot exposure
- Probability-weighted arbitrage opportunities for traders
This moved the business from descriptive analytics to predictive and probabilistic intelligence — something the old stack could never do.
3. AWS Activate Success: $200k+ in Credits & Institutional Support
The rebuild unlocked over $200k in AWS Activate credits, accelerating development without capital pressure.
This success also helped:
- Secure a place in the Startup Bootcamp accelerator.
- Establish a formal partnership with Monash University to create an internship program.
- Turn that internship program into the primary talent pipeline for engineering — a repeatable, low-cost source of capable developers who continued contributing across multiple years.
This combination of cloud credits + accelerator + university partnership reduced cost-to-build by an estimated 60–70%.
4. Enterprise Impact: A Procurement Intelligence Engine
The new platform became the central procurement and reporting system for multiple major clients across banking, corporates, and nonprofit organisations.
Key outcomes delivered:
1. Procurement Strategy Modelling
- Multi-year scenario simulations
- Contract vs spot risk comparison
- Hedging and arbitrage opportunities projected with confidence intervals
- Exposure reporting for executives and boards
2. Network Behaviour Analytics
- Real-time insights into network loss factors (DLF/MLF)
- Regional and site-level risk scores
- Predictive alerts for material changes impacting future bills
3. Intelligent Invoicing & Validation
- Automated ingestion and cross-validation of invoices
- Detection of mismatches, anomalies, and billing errors
- Serverless reporting distributed automatically to stakeholders
4. Enterprise-Grade Reporting
- Custom BI dashboards refreshed in real time
- Compliance reporting for auditors and regulators
- Automated summaries for procurement committees
The platform transitioned from “a reporting tool” to the decision engine for energy procurement.
5. Commercialisation & Enterprise Service Layer
What began as an internal tool evolved into a full enterprise intelligence service offering:
- Data infrastructure as a managed service
- Forecasting and modelling engine as a subscription
- Invoicing validation and anomaly detection
- Procurement dashboards and strategy reporting
Large enterprises adopted it because it removed millions in risk and replaced legacy internal systems that had never been modernised.
6. Why This Build Stands Out
Built from a tiny start
The project started with one Power BI file and an old SQL server. No team. No budget. No roadmap.
Evolved into a modern, elastic platform
Cloud-native, event-driven, modular, and capable of ingesting and analysing years of energy market behaviour.
Direct commercial value
- Enabled better procurement decisions across multiple million-dollar portfolios.
- Reduced billing errors and prevented cost leakage.
- Created a repeatable energy intelligence product that enterprises purchased as a service.
Talent engine
Monash University partnership delivered ongoing engineering talent and reduced development cost significantly.
Future-proof architecture
Serverless, scalable, and designed for forecasting, sensitivity analysis, and market simulation — something few enterprise energy tools can handle even today.
7. Summary
This project represents the classic arc of a well-executed digital transformation:
- Started as a rigid SQL + Power BI reporting stack.
- Rebuilt into a cloud-native forecasting and procurement intelligence engine.
- Leveraged over $200k in AWS credits and accelerator support.
- Established a university-driven talent pipeline.
- Commercialised into a recurring enterprise service adopted by large organisations.
In the end, it became the invisible brain powering procurement decisions, invoicing accuracy, risk management and long-range strategy — a quiet but critical engine in the business operations of major Australian enterprises.