Derisk360
02 · DATA

Enterprise Data Management

Agentic approach to enterprise data management — curation, quality, and scale.

Enterprise data management applies agentic methods to curate, govern, and operate data at scale — supporting data product design, field mapping, and continuous quality across the stack.

OVERVIEW[ 01 / 05 ]

What this accelerator delivers.

Enterprise data estates are too large and too fragmented for manual curation alone. Static catalogues go stale within weeks; data quality issues surface only when agents fail in production. This accelerator embeds agentic methods into data management — accelerating data product design, continuous quality checks, and field-level governance at scale. Forward Deployed Engineers work alongside your data teams to move from passive catalogues to living data products that feed production agents with qualified, auditable data. The result is not another MDM shelfware deployment — it is an operational data management capability that keeps pace with agentic workloads and regulatory scrutiny in banking, insurance, and other regulated industries.

Key takeaways

Agentic curation and quality workflows

Data product design aligned to value streams

Scale across complex regulated estates

Continuous quality, not one-off catalogues

DELIVERABLES[ 02 / 05 ]

Concrete artefacts, not slide decks.

01 / ANALYSE

Data estate assessment

Agent-assisted analysis of data assets, quality gaps, and product opportunities across the estate.

02 / CURATE

Agentic curation workflows

Automated mapping, classification, and quality checks embedded in the data lifecycle.

03 / PRODUCT

Data product specifications

Governed data products designed for specific agent workloads and value streams.

04 / OPERATE

Quality monitoring dashboard

Continuous data quality metrics and alerting for production agent dependencies.

HOW WE DELIVER[ 03 / 05 ]

Four phases to production go-live.

01 / PLUG IN

Embed & discover

FDEs embed with your data team to assess the estate and prioritise data products for agent workloads.

02 / INGEST

Unify context

Connect source systems into a governed context layer — MCP, knowledge graphs, and field mapping in your environment.

03 / BUILD

Configure & evaluate

Configure agentic curation workflows, data product specs, and quality monitoring for production.

04 / RUN

Deploy & monitor

Go live securely in your cloud with FDEE-led monitoring, continuous evaluation, and proactive tuning.

USE CASES[ 04 / 05 ]

Where this accelerator applies.

BANKING

Regulatory reporting data products

Curate and qualify data products for financial reporting and reconciliation agents.

INSURANCE

Actuarial and claims data curation

Agentic quality workflows for actuarial models and claims processing data.

CROSS-INDUSTRY

Enterprise data product factory

Repeatable pattern for designing and operating governed data products at scale.

PROVEN[ 05 / 05 ]

Production outcomes, not pilot metrics.

50%

Reduction in manual data mapping effort via agentic curation workflows.

Faster data product delivery compared to traditional catalogue approaches.

99.9%

Data quality threshold maintained for production agent workloads.

See customer outcomes →

Ready for an AI implementation partner?

Book a discovery call and we'll map your highest-value use case — and exactly how we get it into production.

AGENTS DEPLOYED IN PRODUCTION · MONITORED 24/7

Frequently asked questions

How does agentic data management differ from traditional MDM?
Agentic data management embeds AI-assisted curation, mapping, and quality workflows into the data lifecycle — accelerating data product delivery rather than maintaining static catalogues.
Can this work with our existing data catalogue?
Yes. The accelerator enhances and operationalises your existing tools — connecting catalogues to live agent workloads with continuous quality checks.
Who operates data products after go-live?
FDEs transfer operational knowledge to your team during delivery. Managed AI services can provide ongoing monitoring if needed.
What industries benefit most?
Regulated industries with complex data estates — banking, insurance, and financial services — where data quality directly impacts compliance and agent accuracy.