From data strategy to production deployment — senior-led, outcome-first, delivered with the rigour of Big 4 consulting. Every engagement. Every time.
We help Australian businesses move from AI curiosity to AI capability — building production-grade models, LLM integrations, GenAI workflows, and autonomous agent systems that generate real, measurable commercial value.
Most AI projects stall between prototype and production. The gap isn't technical — it's the absence of engineering rigour, commercial alignment, and ML operations discipline. We close that gap. Our practitioners have built and deployed LLM-powered insights layers, pricing optimisation engines, churn propensity models, demand forecasting systems, and GenAI-driven reporting automation — in production, at scale, under real enterprise pressure.
We don't run endless discovery workshops. We assess your data readiness, identify high-ROI use cases, build a working prototype fast, then harden it for production. Commercial outcome first, technology second.
Built on Microsoft Fabric — pulled structured medallion data, passed contextualised JSON to an LLM, generated natural-language executive commentary and anomaly narratives. Eliminated manual reporting effort across C-suite teams.
ML-driven pricing models for a $1.5B national retailer — incorporating macro and microeconomic factors to dynamically recommend optimal price points, contributing to measurable margin improvement.
End-to-end ML pipeline using XGBoost and LightGBM — from feature engineering to production API deployment, automated retraining, and performance monitoring dashboards.
Designed and implemented GenAI agent-based workflows that automate insight generation, reducing analyst manual effort. Supports self-service analytics with natural language querying of enterprise data.
Structured workshops to surface AI opportunities ranked by business impact, data readiness, and implementation complexity. No ideas without a business case.
Before any modelling, we validate that the right data exists, is accessible, and meets quality thresholds. We fix data problems before they become model problems.
We build a working proof of concept fast — enough to validate the approach and build confidence before full investment. Speed to insight matters.
We harden models for production: containerisation, API integration, CI/CD pipelines, monitoring, automated retraining, and performance benchmarking under load.
Model cards, monitoring alerts, retraining triggers, and team training — so your organisation owns the system, not just the output.
We build next-generation business intelligence that goes beyond dashboards — creating embedded analytics, real-time intelligence layers, AI-augmented reporting, and self-service data cultures that give every team the insight to act.
The era of static reports and weekly BI packs is over. Modern BI is real-time, self-service, AI-augmented, and embedded into the workflows where decisions happen. We've overseen thousands of dashboards in production, built enterprise KPI frameworks from scratch, and led the analytics practices for organisations generating billions in annual revenue — from national retailers to Fortune 300 APAC enterprises.
CDC pipelines feeding live dashboards — moving from T+1 batch reporting to sub-minute insight. Built on Fabric, Kafka, and streaming SQL.
LLM-powered narrative generation, anomaly detection in dashboards, and natural language interfaces so any user can query data without SQL.
Single source of truth for business metrics using dbt metrics, Microsoft Fabric semantic models, or Looker LookML — eliminating dashboard sprawl and metric inconsistency.
Analytics embedded directly into operational applications and mobile-optimised — meeting users where decisions happen, not in a separate BI portal.
Map decision flows, identify critical KPIs, and define what "trusted data" means for your organisation.
Audit sources, quality, and infrastructure. Identify gaps before any build starts.
Build the right data model — not a template. Reflect your business structure.
Continuous stakeholder feedback. No big-bang launches. Working dashboards in days, not months.
Full documentation, governance model, and team training so your organisation owns it long-term.
We build the data pipelines and infrastructure your analytics, AI and operations depend on — reliable, tested, observable, and built for long-term ownership by your team.
Great analytics and AI are only as good as the data flowing into them. We design and build robust ETL/ELT pipelines, streaming architectures, CDC implementations, and data quality frameworks that operate at enterprise scale. We've managed the entire ETL estate for billion-dollar businesses and led full migrations to Microsoft Fabric, achieving 80% ETL runtime reductions in production.
Catalogue all sources, schemas, refresh frequencies, ownership, and quality issues before any build.
Design ingestion patterns, transformation logic, orchestration, and monitoring upfront.
Modular, tested, version-controlled code with robust error handling — not brittle scripts.
Automated checks at every layer — row counts, null rates, referential integrity, business rule validation.
Observability tooling, alert config, and full documentation for your team to own ongoing.
We design the data platforms your organisation needs to scale — from greenfield lakehouses to modernising tangled legacy estates — with phased roadmaps that deliver value at every step.
Poor architecture is the most expensive invisible problem a business can have. We have hands-on experience building medallion architectures on Microsoft Fabric, designing cloud data warehouses across Azure, Snowflake, Redshift, and Databricks, and implementing data governance frameworks that pass regulatory scrutiny.
Led Fortune 300 APAC enterprise migration to Fabric using Bronze/Silver/Gold medallion model — 80% ETL runtime reduction, near real-time CDC, unified governed source of truth.
Designed and built purpose-built data marts for Finance, Marketing, Merchandise, Purchasing, and Operations at a $1.5B retailer — enabling full self-service analytics.
Established governance including data ownership, lineage tracking, RBAC security, metadata standards, audit controls, and monitoring/alerting.
We plan and execute complex data migrations — legacy on-prem to cloud, platform-to-platform, ERP, or M&A consolidation — with structured methodology, full reconciliation, and zero data loss.
Data migration is one of the highest-risk projects a business can undertake. Done poorly, it causes data loss, extended downtime, compliance exposure, and failed programmes. We have led end-to-end migrations for major Australian businesses — including full on-premise warehouse to Microsoft Fabric migrations — with proven reconciliation frameworks at every stage.
Inventory all data assets, assess volume and complexity, identify regulatory constraints. Risk-ranked migration plan.
Profile source data for quality issues, duplicates, gaps — fix at source, not at destination.
Transformation rules, load sequencing, parallelism strategy, and right tooling selection.
Multiple test runs with full reconciliation — row counts, checksums, business rule validation — before production.
Detailed runbook, real-time monitoring, clear rollback plan. End-to-end validation post-cutover.
We manage, optimise, and evolve your data and analytics platforms — Microsoft Fabric, Snowflake, Azure, Databricks, Power BI, and more — so your team can focus on insight, not infrastructure.
Enterprise data platforms don't run themselves. They need active governance, performance tuning, cost optimisation, user management, security, and ongoing evolution as your business grows. We provide the specialist platform management capability that keeps your data infrastructure performing at its peak — whether you need a fully managed service or expert oversight of your own team.
End-to-end Fabric workspace management, OneLake governance, pipeline monitoring, Synapse Analytics, Azure Data Factory, and cost optimisation across the Azure data stack.
Virtual warehouse sizing, query optimisation, credit consumption management, RBAC security, data sharing setup, and performance monitoring for Snowflake environments.
Cluster management, job scheduling, Delta Lake maintenance, Unity Catalog governance, MLflow model management, and cost control across Databricks workspaces.
Tenant governance, workspace management, capacity monitoring, dataset refresh orchestration, row-level security, gateway management, and deployment pipeline setup.
Redshift cluster management, AWS Glue ETL monitoring, S3 data lake governance, Athena optimisation, and IAM security management across the AWS data ecosystem.
BigQuery project management, slot reservation, cost controls, dataset governance, Looker administration, and Dataflow pipeline management on GCP.
We build the models, frameworks, and data infrastructure financial institutions need to make better lending decisions, manage portfolio risk, and meet APRA, IFRS 9, and Basel regulatory requirements.
Our credit risk practice is built on real delivery — PD, LGD, EAD model development at a major Australian bank and Big 4 consulting, portfolio management through COVID-19 at a business bank, credit scoring and collections strategy at a leading fintech, and regulatory model work across banking, insurance, and superannuation. We know what regulators expect.
We build the data foundation, pricing models, and analytics infrastructure that e-commerce businesses need to grow revenue, optimise inventory, and understand customers at depth.
We've worked at the coalface of Australian e-commerce — as the analytics lead for one of Australia's largest online marketplaces at over $2B revenue, with 40M+ products. We've built price sensitivity models, led competitive price-matching engines, and driven analytics programmes that delivered major YoY sales growth.
We embed experienced consultants directly into your team — filling capability gaps, accelerating delivery, and building lasting internal expertise without the overhead of a permanent hire.
Sometimes you don't need a full engagement. You need a senior data engineer for four months, or an analytics lead to mentor your team through a critical delivery. Our consultants work in your tools, on your timeline, with consulting quality assurance behind them.
Define the skills gap, deliverables, team context, and success criteria — so we match the right person, not just the right title.
We present matched consultants with relevant experience. You choose who you want.
Our consultants hit the ground running. Typically productive within the first two weeks.
Thorough documentation and handover so your team is stronger, not more dependent, when we leave.
Tell us about your challenge and we'll advise the right approach. No sales pitch — just honest guidance.