What We Do

Data & AI Services

From strategy to implementation, we help organisations build data foundations that deliver measurable business value — with clear timelines and tangible outcomes.

Jump to: Engagement Approach
2 weeks

Data Foundations Assessment

Comprehensive assessment of your data maturity with a prioritised roadmap for improvement.

Who this is for

Organisations seeking clarity on their data capabilities and a clear path forward.

Clear strategic directionStakeholder alignmentQuick wins identified

Deliverables

What you'll receive

  • Current state assessment across 5 dimensions
  • Maturity scoring and benchmarking
  • Gap analysis and opportunity identification
  • Prioritised improvement roadmap
  • Executive presentation deck
Discuss This Service
6–12 weeks MVP

Modern Data Platform Build

Design and implement a production-ready modern data platform using medallion architecture.

Who this is for

Teams ready to modernise their data infrastructure with Snowflake, Databricks, or cloud-native solutions.

30–50% faster data deliveryUnified data platformSelf-service analytics ready

Deliverables

What you'll receive

  • Platform architecture and design
  • Bronze/Silver/Gold layer implementation
  • Data ingestion pipelines
  • Governance and access controls
  • Documentation and runbooks
  • Team enablement sessions
Discuss This Service
4–8 weeks

Data Trust & Quality Operating Model

Establish a sustainable data quality framework with automated monitoring and clear ownership.

Who this is for

Organisations struggling with data trust, inconsistent quality, or regulatory compliance.

20–40% fewer data defectsRegulatory confidenceTrusted data assets

Deliverables

What you'll receive

  • Data quality framework design
  • Automated DQ monitoring setup
  • Quality rules and thresholds
  • Ownership and stewardship model
  • Incident response playbook
  • Metrics dashboard
Discuss This Service
PoC in 4 weeks, scale in 8–12 weeks

Agentic Automation for Data Delivery

Deploy AI agents to automate data quality, pipeline monitoring, and routine data operations.

Who this is for

Forward-thinking teams ready to operationalise GenAI for data management.

60%+ reduction in manual effortFaster issue resolutionScalable automation

Deliverables

What you'll receive

  • Use case identification and prioritisation
  • AI agent architecture design
  • PoC development and testing
  • Production deployment
  • Monitoring and feedback loops
  • Team training on agent management
Discuss This Service
4–6 weeks

Governance for GenAI & Data Products

Establish policies, controls, and enablement for responsible GenAI adoption.

Who this is for

Enterprises adopting GenAI who need governance without blocking innovation.

Responsible AI adoptionRisk mitigationAccelerated innovation

Deliverables

What you'll receive

  • GenAI governance framework
  • Policy and control documentation
  • Risk assessment methodology
  • Approval and oversight processes
  • Enablement guidelines
  • Stakeholder communication pack
Discuss This Service
How We Engage

Discovery → PoC → Implementation

A proven three-phase approach that de-risks delivery and accelerates time to value.

2 weeks
6 weeks
12+ weeks

Typical end-to-end: ~20+ weeks depending on scope and complexity

Discovery Sprint2 weeks
2 weeks

Discovery Sprint

Activities

  • Stakeholder interviews + current-state assessment (data, platform, operating model)
  • Use-case prioritisation + value sizing
  • Target architecture + security review (incl. data handling + LLM boundaries)
  • Data inventory + profiling (sample where possible)
  • Delivery plan + backlog + success metrics

Outcomes

  • Agreed priorities + success criteria
  • Target-state architecture + roadmap
  • Delivery plan + resourcing + timeline

Deliverables

Assessment reportArchitecture diagramBacklogSuccess metricsRisk & controls

Decision Gate

Proceed to PoC with signed scope and measurable success criteria

Proof of Concept6 weeks
6 weeks

Proof of Concept

Activities

  • Implement 1–2 accelerators end-to-end on sample or limited real data
  • Stand up environments + CI/CD baseline + governance guardrails
  • Produce working outputs (models / pipelines / DQ rules / lineage)
  • Demo iterations with weekly feedback loops
  • Define production hardening requirements

Outcomes

  • Working pilot proving feasibility + value
  • Clear production backlog and acceptance criteria
  • Effort/TCO comparison vs baseline approach

Deliverables

Working pilotDemo packRunbook draftPoC reportProduction backlog

Decision Gate

Proceed to Implementation based on pilot success + sponsor sign-off

Implementation12+ weeks
12+ weeks

Implementation

Activities

  • Scale from PoC to production-grade solution (pipelines, models, governance)
  • Integrate with enterprise tooling (Snowflake/Databricks/dbt, catalog, monitoring)
  • Security hardening, testing, performance, reliability (SLOs)
  • Operating model: ownership, SLAs, support, change management
  • Enablement: documentation + training + handover

Outcomes

  • Production rollout with measurable KPIs
  • Sustainable operating model + controls
  • Handover completed; teams enabled to run independently

Deliverables

Production releaseMonitoring & SLOsRunbooksDocumentationTraining

Decision Gate

Transition to BAU + continuous improvement roadmap

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Flexibility

Engagement Models

Choose the approach that fits your needs and context.

Project-Based

Defined scope and timeline for specific initiatives.

Best for: Platform builds, assessments, PoCs

Retainer

Ongoing advisory and support on a flexible basis.

Best for: Strategic guidance, fractional CDO

Workshop

Intensive sessions for strategy or capability building.

Best for: AI readiness, team upskilling

Ready to Get Started?

Book a 30-minute intro call to discuss your challenges and explore how we can help.

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