Data-Driven AI applies our structured and proven project delivery methodology, known as the Data-Driven AI Project Methodology. It combines the discipline of our ISO 9001-certified Quality Management System with the flexibility of Agile practices. Our approach has been refined through years of delivering successful, cost-efficient modern data platform implementations for government and enterprise clients.
This methodology gives our clients the assurance of a repeatable, transparent, and collaborative system that consistently delivers on time, within scope, and to a high standard. It is designed to deliver projects successfully, efficiently, and safely while embedding governance, quality, and cultural adoption for long-term sustainability.
The Data-Driven AI Project Methodology follows five integrated phases. Each phase within the Framework is designed to address specific needs within the project lifecycle. By following this framework, we deliver repeatable, scalable, and secure analytics solutions tailored to your business objectives.
Our methodology follows five integrated phases, designed to address specific needs within the project lifecycle and each with defined entry and exit criteria, quality checkpoints, and peer reviews to ensure predictability and traceability:
1. Discovery and Assessment
We analyse the current environment, engage stakeholders, identify pain points and KPIs, and confirm success measures, user and data requirements. This phase defines the roadmap, scope, and plan for the analytics and cloud transition. Deliverables: Project Charter, Scope Statement, RAID register, initial architecture review
2. Solution Design
We design the end-to-end architecture for ingestion, storage, processing, governance, reporting and integration plan. All designs are reviewed and approved to ensure they meet security, compliance, and NSW Government standards. Deliverables: High-Level and Low-Level Design, Architecture Diagrams, Security and Compliance Plan.
3. Implementation & Testing
We build and test iteratively using Agile sprints (typically 2–4 weeks). Each sprint produces tangible outcomes such as data pipelines, medallion layers, or semantic models, supported by sprint planning, daily stand-ups, reviews, and retrospectives. Deliverables: Configured environments, tested pipelines, dashboards, sprint reports.
4. Handover & Documentation
We deliver full documentation, guides, and training to enable smooth operational handover. A post-implementation architecture review validates the solution against best-practice Azure principles. Deliverables: Knowledge transfer sessions, user guides, post-implementation review.
5. Maintenance & Support
We resolve post-deployment issues, provide SLA-based support, and conduct periodic health and architecture reviews to keep the platform secure, reliable, and optimised. Transition to our managed support service delivered through JIRA Service Management (or any ITSM tool chosen), ensuring continuity and rapid issue resolution. The same engineers who built the platform provide ongoing support, guaranteeing deep system knowledge and consistency. Deliverables: SLA-based support reports, periodic health checks, enhancement roadmap.
Quality and governance are embedded in every aspect of our implementation methodology. We are certified in ISO/IEC 27001:2022 for Information Security Management Systems, ISO 9001:2015 for Quality Management Systems, and our upcoming certification in ISO 42001 for AI Management, expected by the end of the fiscal year. This ensures transparent reporting, rigorous quality control, consistent documentation practices and milestone delivery across the project lifecycle.
Documented processes and formal approval steps are enforced.
RACI matrix establishes clear accountability.
RAID register is actively maintained and reviewed weekly.
Peer review and testing are completed before final sign-off.
Azure Well-Architected Reviews ensure optimal performance.
FinOps reporting supports continuous cost optimisation.
PMO and delivery leadership maintain complete oversight.
Schedules, resources, and milestones are effectively managed.
Governance reporting is conducted regularly to track progress.
Retrospectives and lessons learned drive ongoing improvement.
Structured feedback loops enhance delivery quality.
Business continuity measures ensure uninterrupted operations.
Risks are identified early and assessed continuously.
RAID register is maintained and reviewed weekly.
Measures reduce impact on scope, schedule, cost, and quality.
Security aligns with ISO 27001 and protects key information assets.
RBAC, secure CI/CD pipeline, and encryption strengthen security posture.
Logging, monitoring, and privacy controls ensure full traceability.
Our Data-Driven AI Project Methodology is the foundation of our engagement model. It ensures every interaction with the customer is structured, transparent, and aligned with best practice delivery principles. Our engagement process extends the methodology into practical steps for on-demand services:
Under the Account Manager’s oversight, our delivery team comprises specialists aligned to your requirements:
SLA tiers define coverage, response time, and monthly cost.
Enables predictable support and proactive monitoring.
Ensures fast resolution for BAU issues and enhancements.
Used for defined initiatives with clear scope and timeline.
Pricing aligned to deliverables and effort required.
Provides transparency, accountability, and measurable outcomes.
Effective and timely communication is one of the strongest predictors of on-time project completion. Our approach ensures that Camden Council receives clear, consistent information at every stage, with escalation pathways and governance integrated into Data-Driven AI Project Methodology and Agile delivery practices.
1.Key Principles
2.Communication Cadence
Meetings
Reports
o Detail progress, next steps, risks, issues, providing full visibility across milestones and dependencies.
o Include resource hours and lessons learned
