Healthcare solutions
Real-time Analytics for Healthcare
If you're investing in real-time analytics for health systems, you've probably already seen a few proofs-of-concept that never made it to production. Beryl Analytics specialises in the messy middle — turning prototypes into reliable systems your operators actually use.
Why healthcare teams choose Beryl Analytics for real-time analytics
- Built for compounding value. Each real-time analytics engagement leaves health systems with infrastructure that accelerates the next one — shared feature stores, reusable pipelines, documented data contracts.
- Real handover. We pair your team into the build from day one. By go-live, they own the system. We're optional from then on.
- Practical AI. We've shipped LLM-augmented analytics where they help, and stayed with simpler models where they outperform. Hype is not a strategy.
- Audit-friendly. Every model decision is traceable. Compliance and risk teams stop blocking — they start enabling.
- Track record. 1,000+ models in production. Across heavy-industry, regulated, and consumer domains.
How we deliver real-time analytics engagements
- 01
Data audit (week 1)
A focused review of what data you have, where it lives, and what shape it's in. Outputs a written read with the gotchas and where to start.
- 02
Contract & instrument (weeks 2-3)
We formalise the inputs the system will depend on — schemas, freshness SLAs, ownership — and instrument anything missing. No model without solid inputs.
- 03
Model + interface (weeks 4-7)
The model itself plus the surface your operators will actually use. Built together so the analysts who debug it know exactly what each output means.
- 04
Soft launch & calibration (weeks 8-10)
Live in a small slice of the business. We watch every decision the system informs, calibrate, and only then expand.
- 05
Full rollout
Scale to the full surface area with documentation, training, and an on-call playbook your team owns end-to-end.
Frequently asked questions about Real-time Analytics for Healthcare
How long does a typical Real-time Analytics engagement take for a healthcare business?
Most real-time analytics projects for health systems land a working production slice within 4-6 weeks, then harden and expand over the following 8-12 weeks. Larger healthcare programmes that touch multiple business units take 4-6 months end-to-end.
What data do you need to start a Real-time Analytics project in healthcare?
Minimum viable inputs are 12-18 months of historical transactional or operational data, basic entity reference tables, and access to the systems that will consume the output. We can work with messy data — cleaning is part of the engagement.
Can Beryl Analytics integrate real-time analytics with our existing health systems systems?
Yes. We're tool-agnostic and have integrated with Snowflake, BigQuery, Databricks, Salesforce, SAP, Oracle, custom in-house platforms, and dozens of healthcare-specific systems. Insights surface inside the tools your operators already use.
How do you measure success on a Real-time Analytics engagement?
Before we model anything, we agree the business decision the output will change and the dollar metric we're targeting — revenue lifted, cost avoided, or risk reduced. Real-time Analytics engagements in healthcare typically return 4-12x within the first year.
Do you work with healthcare businesses outside major NZ and AU cities?
Yes. We deliver remotely across New Zealand and Australia and visit on-site for discovery, key workshops, and go-live. Distance is not a blocker — many of our highest-impact real-time analytics engagements have been with regional health systems.