Data Engineering
Custom pipelines that pull data out of wherever it currently lives, clean it, and connect it to the systems that need it. Spreadsheets, disconnected software and manual re-entry are the problem behind almost every automation and AI project.Pipelines that pull your data together, clean it, and connect it.
Built for how your data actually moves.
A fixed, scoped process — no open-ended engagements.
Assess & define
Review where data lives, how it moves, and where the gaps and manual steps are; then agree the target architecture and a governance baseline (naming, quality rules, access) before anything gets built.
Design the pipeline
Choose the right pattern for your systems: batch ETL, ELT, or real-time streaming, depending on volume and latency needs.
Build & validate
Construct the pipelines with quality and validation checks built in at the point of ingestion, not bolted on after.
Migrate & support
Move data across with minimal disruption, verifying accuracy before the old process is retired, then ongoing monitoring as your sources and volumes change.
What this looks like for you.
A few examples of what this actually looks like once it's live.
MANUAL EXPORTS
No more copying numbers between spreadsheets, invoicing tools and your CRM by hand every week.
DISCONNECTED SYSTEMS
Your sales, ops and finance tools finally talk to each other, without a person in the middle.
CLEAN REPORTING
One pipeline feeding your dashboards, instead of three versions of the truth in three files.
READY FOR WHAT'S NEXT
A proper data foundation, so the AI or automation project you want next isn't blocked on "first, sort out the data."
Scope, timeline and price.
Messy data scattered across systems, with no structure behind it.
Your data migrated into a single source of truth: organised, cleaned, and ready to plug into the systems you already run.
TYPICAL DURATION
2–8 weeks, depending on data volume.
PRICING
Fixed fee.
ENTRY OFFER
Data audit call. Current state, sources, volume.
TRACK RECORD
We’ve structured and standardised product data at scale for AI consumption.