Insights

Notes on data, artificial intelligence and the architecture of enterprise platforms.

Why enterprise AI needs a platform with data, model, agent and governance layers rather than a scattering of disconnected models.

When one customer has five identities in five systems, no report, decision or customer experience can be trusted.

Authentication is only half the problem; governing who should have which access, and why, is the harder half.

API gateways and events are not rivals; one answers the question now, the other tells everyone what has just happened.

A 360-degree customer view is not a dashboard; it is the product of a party master, a data lake and an analytics layer working together.

Computer vision turns a car park from a physical space into a data stream, provided the architecture behind it is designed properly.

Sensors are the easy part of smart agriculture; the hard part is turning thousands of readings into a decision a farmer will trust.

When a water right becomes a transferable, auditable digital record, it changes from a paper document into a resource-management tool.

A data lake is not a place to dump everything; with the right governance it is the layer that turns raw data into an enterprise asset.

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If your organisation, bank or industry is ready to turn data into decisions, start the conversation here.