We manage the whole data lifecycle — strategy, governance, master data, quality, migration and analytics — so that the analytics and AI you build on top of it can be trusted. Measured against the DAMA-DMBOK2 and DCAM international standards, not against an opinion.
The same customer exists four times across the ERP, the CRM and two spreadsheets. Nobody owns the data, so when a number is wrong there is no one to fix it and no process that stops it happening again. The migration overruns. The dashboards get argued with. And the AI business case quietly dies in a steering committee.
An AI model is a mirror. Point it at unmanaged data and it will reflect that back to you at scale, confidently and fast. Agilus exists to prevent exactly that. We fix the data foundations and build the AI on top — as one engagement, not two.
What we do
Data Strategy & Operating Model
a data strategy that names owners, not just ambitions.
Assess your data management maturity and AI readiness across seven pillars aligned to DAMA-DMBOK2 and DCAM — then fix what the assessment exposes with automated data quality: profiling, cleansing, matching and ruleless anomaly detection. Home of the free AI Readiness Scorecard.
Your data management maturity is scored against DAMA-DMBOK2 and DCAM — international standards you can verify — not a consultancy’s private methodology.
We own the tooling.
DM360 and Supplier360 are built by Agilus. You are not paying us to administer someone else’s licence.
We work the whole stack.
Most firms sell one layer. We work the layer where the problem actually is — and we can prove which layer that is.
We know your data realities.
POPIA, legacy ERP estates, multi-source consolidation, mixed-quality reference data. Global playbooks do not survive contact with them. Ours are built there.
Our Customers Get Results
Organisations that trust Agilus with their data include Liberty, SASSA, Rand Water, DP World, AECI and Anglo American — across financial services, government, utilities, logistics, chemicals and mining.
Tell us what is actually broken — a migration that has stalled, numbers nobody trusts, an AI plan with no foundation under it. Thirty minutes with someone who has fixed it before.