Case studies

Governed AI, delivered.

A sample of recent engagements across financial services, insurance, energy, retail and beyond. Client names are withheld; the outcomes are real.

Financial ServicesAustralia

Governed document-to-AI foundation for advisers

Document retrieval that previously took hours now returns sourced, versioned answers in under four seconds. The answer inconsistencies that regulators had flagged as a control weakness were eliminated, and the architecture became reusable across multiple banking domains including treasury, trade finance and customer onboarding.

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Financial ServicesAustralia

One-month requirements assessment for enterprise migration planning

In approximately one month, produced the requirements artefacts, sequencing and scoping inputs needed for governed multi-partner planning, supporting the bank's ambition to pursue a shorter migration pathway, without delivering or owning the full migration programme.

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Financial ServicesSingapore

MultiRAG architecture & solution design scoping

Produced a clear MultiRAG architecture and solution-design baseline for a governed enterprise AI factory, and scoping and design direction for subsequent delivery teams, not pilot delivery or production rollout.

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Financial ServicesVietnam

Internal RAG quality & latency made measurable

Cut response latency from 35 to 40 seconds to 15 to 18 seconds, roughly 55 percent faster at the midpoint, while making accuracy, retrieval relevance and agent performance continuously measurable.

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InsuranceHong Kong

Agent 360, governed multi-agent insurance AI

Established and demonstrated a governed enterprise agentic AI reference architecture for reasoning across documents and structured business data, forming a foundation for claims and health AI applications and validating reusable patterns for orchestration, governance, evaluation and enterprise tool integration.

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InsuranceAustralia

GenAI VOC & claims intelligence discovery

Produced the business requirements, solution direction and reference architecture needed to support AI-powered claims transcript summarisation and structured information extraction.

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InsuranceAustralia

AI-powered regulatory summarisation for compliance

Reduced compliance review time, increased accuracy and regulatory adherence, and established automated knowledge reuse across departments.

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Energy & ResourcesAustralia

Predictive maintenance foundation for gas compression systems

Detected faults up to seven days in advance across more than 10,000 daily sensor readings per asset, letting engineers move from reactive emergency response to proactive scheduling. Reduced unplanned downtime and delivered real-time anomaly dashboards for ongoing operational awareness.

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Energy & ResourcesAustralia

Operational forecasting from 8-second cycles to real-time

Moved operational forecasting from an approximately 8-second batch cycle to real-time predictions, while strengthening governance, auditability and MLOps resilience for industrial operations.

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Energy & ResourcesAustralia

AI-assisted engineering workflow for well operations

Reduced manual data-validation time across daily and weekly compliance workflows, improved report accuracy with complete audit trails, and enabled near real-time operational insight during shift handovers and daily reviews. Established a reusable evaluation framework since applied to all of the operator's subsequent generative AI initiatives.

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Retail & HospitalityThailand

GenAI product matching at catalogue scale

Runtime collapsed from roughly 30 days to roughly 3, a 90 percent cycle-time reduction, with every run now governed, measurable and auditable end to end. Unlocked product substitution, assortment optimisation and competitive intelligence at catalogue scale.

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Retail & HospitalitySingapore

Pilot ML hardened for production delivery

Converted the pilot into an operationally robust delivery model, raising confidence in repeatability, governance, testing and responsible future scaling.

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Retail & HospitalityMultiple markets

Environment-aware data governance & drift monitoring

Delivered cross-environment drift management exceeding industry best practice, automated retraining with zero manual intervention, and enhanced compliance reporting for every production model event.

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Retail & HospitalityMultiple markets

Enterprise RAG & model gateway for unified ML operations

Unified ML operations across business units, reduced model deployment time, established continuous compliance through governed pipelines, and enabled measurable ROI through reusable AI components and workflows.

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ManufacturingNew Zealand

From ad-hoc notebooks to an ML operating model

Established a reusable blueprint so future teams can build, deploy, monitor and govern ML and generative AI consistently, cutting reliance on one-off development.

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TechnologyUnited States

Enterprise Business AI & Genie Foundation

Established the implementation blueprint for an enterprise Business AI platform and reusable frameworks for governed AI deployment, evaluation and operationalisation, targeting 500 to 1,000 business users.

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Enterprise R&DMultiple markets

A modular RAG framework for enterprise knowledge systems

Reduced new client onboarding from weeks to hours, provided enterprise auditability through an integrated evaluation layer, and formed the baseline for all subsequent RAG deployments across industries.

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Logistics & TransportationMultiple sites

Computer vision object detection across a logistics network

Enabled near-real-time monitoring of people and vehicle events with structured analytics, delivered as a reusable framework offering operational transparency and actionable metrics.

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FintechMultiple markets

An intelligent data-mining agent for KYC and risk

Automated cross-validation significantly reduced manual fact-checking, improved data freshness and accuracy, and created an adaptive intelligence layer over web data extraction that handles search complexity and record updates on its own.

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HealthcareMultiple markets

NLP preprocessing for a healthcare GenAI assistant

Provided a high-quality text corpus prepared for generative-model training, enabled downstream generative tasks with clean, consistent input, and formed the backbone for enterprise-grade NLP modelling with data readiness, governance and consistency built in.

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