Four practices, one conversation.
Senior throughout. We handle the full project — one point of contact, full accountability. Most clients start with one practice and grow from there.
Solution architecture
Platform design, technology selection, the master plan. We start with the question, not the stack. The output: an architecture you can defend to your board and execute with us or without us.
What's included
- 01 Discovery & current-state assessment
- 02 Reference architecture and tooling shortlist
- 03 Cost & scale modelling at 1× and 3× current load
- 04 Phased delivery roadmap
- 05 Build/buy/keep recommendation per layer
Not sure if this is the right starting point? Most clients aren't, on day one.
Talk about solution architecture →Data engineering
Pipelines, integrations, ELT, streaming, IoT. Cloud-native or on-prem — whatever fits the data, the regulations, and the budget. We write what's needed, no more.
What's included
- 01 Ingestion from databases, APIs, files, IoT
- 02 ELT and orchestration — dbt, Airflow, native cloud
- 03 Streaming pipelines for operational data
- 04 Quality, monitoring, and alerting from day one
Not sure if this is the right starting point? Most clients aren't, on day one.
Talk about data engineering →Dashboards & reporting
Operational dashboards that get opened daily. Usually the fastest way to demonstrate the platform is real. Power BI, Tableau, Looker — your choice, or ours if you'd rather we picked.
What's included
- 01 Operational dashboards for daily use
- 02 Executive reporting against agreed KPIs
- 03 Self-service templates and a small training session
- 04 Refresh, governance, and access — handed over clean
Not sure if this is the right starting point? Most clients aren't, on day one.
Talk about dashboards & reporting →Data analytics
Patterns, KPIs, self-service intelligence. Where the data starts answering questions you didn't know to ask. We apply AI where it adds something. We tell you when it doesn't.
What's included
- 01 Diagnostic and exploratory analysis
- 02 KPI design and benchmark setting
- 03 Forecasting and predictive modelling, where the data supports it
- 04 Self-service enablement for your team
- 05 AI applied where it earns its place — not as default
Not sure if this is the right starting point? Most clients aren't, on day one.
Talk about data analytics →Pick a practice, or we'll pick the right starting point.
Tell us where the data lives and what's getting in the way. We'll tell you what we'd do.