EXPERTISE
Data engineering & platforms
Build a traceable path from operational records to reliable reporting, with explicit quality and recovery rules.
Context shapes the solution.
Start with the problem, then agree the work. Architecture reviews, engineering design and implementation are scoped around your constraints and operating responsibilities.
Systems & Data Architecture Review
A focused starting engagement for organizations facing fragmented systems, unreliable reporting or difficult technology decisions.
Scope, access, deliverables, timing and fees are agreed in writing before work begins. Implementation is scoped separately.
Potential deliverables
- Source-to-report lineage and metric definitions
- Data models, pipeline design and reconciliation rules
- Quality checks, exception handling and replay strategy
- Ownership, freshness targets and recovery runbook
Scope, access, deliverables, timing and fees are agreed in writing before work begins. Implementation is scoped separately.
Prepare the foundations for AI.
Assess data quality, access, provenance and availability before proposing an AI use case. Define evaluation criteria and human oversight appropriate to the risk.