The model is rarely the problem. The invoice that never reached the pipeline, the case file in a format nobody indexed, the sensor feed with no lineage — that is what stalls AI in production.
This service line makes your data a standing asset for AI: ready, governed, retrievable, and traceable — on your cloud, in your jurisdiction, or fully on-premise.
Outcome
Trusted, AI-ready data and decisions traceable to source.
Data readiness
Inventory of the sources a use case actually needs, their quality, ownership and access — and the gaps that would stall a model.
Pipelines & lakehouse
Multimodal pipelines, feature pipelines and lakehouse patterns models can use, with lineage and versioning built in.
Data governance
Classification, residency controls and access policy — regulated data stays where it must, with evidence by default.
Vector & retrieval
Retrieval systems over documents and knowledge, so agents answer from your record rather than the model's memory.
Annotation & synthetic data
Labelled and synthetic data produced to the spec a model needs, with quality and drift monitoring.
Decision reporting
Every automated decision traceable to the data that produced it — the audit trail governance asks for.
Data for AI is the first stage of the same stack we run for self-hosted and in-jurisdiction deployments, so what we build here carries straight into training, fine-tuning and serving.
Where it runs
- Your cloud — OCI, AWS, Azure or GCP landing zones
- Sovereign cloud with data-residency evidence by default
- On-premise and air-gapped, for data that cannot leave
ARB Corporation · ASX-listed manufacturer
An intelligent processing pipeline integrated with JD Edwards — data validated and coded against the system of record before a person sees it.
Read moreState pathology service
Clinical document intelligence — extraction, structuring and coding of pathology reports.
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