One Framework.
Many Domains.
A pluggable diagnostic analytics platform
with AI as the domain expert —
and nuMetrix as the first proof.
Always a framework.
From the start, the idea was an application framework
with a strong processing pipeline, a rich frontend,
and AI playing the role of subject matter expert.
The hospital was the first domain — not the only one.
Framework + Domain + AI
Taxonomy engine. Explorer shell.
Multi-tenant isolation.
How to ingest, validate, diagnose, and present.
Source-system mappings.
Interpretation. Regulatory context.
What to look for and why it matters.
Data formats. Business logic.
Medical knowledge. Regulations.
Who brings the domain knowledge — at scale.
nuMetrix — hospitals and material flow
including real SZO data
OPALE · SAP · Navision
compiled from YAML
probes → hypotheses → diagnoses
A full diagnostic pipeline for hospital material flow analytics.
Built on the jinflow framework. The first instantiation, not the last.
Engine vs. Domain
80% engine. 20% domain knowledge. By design.
The engine doesn't know what a “case” is.
The domain pack does.
Probe compiler (YAML → SQL)
Hypothesis + Diagnosis compilers
Findings contract (10 standard columns)
Taxonomy engine (tree + closure table)
Explorer (probe discovery, interpretation, i18n)
Multi-tenant platform layer
Orchestration (Dagster, rebuild scripts)
Knows how. Knows nothing about why.
Source-system dispatch (column mappings)
Probe YAML definitions (business rules)
Hypothesis + Diagnosis YAMLs
Registry (tri-lingual display text)
Interpretation rules (context overrides)
i18n labels
Synthetic data profiles
Knows why. All declarative. All swappable.
A directory. YAML and JSON. No code.
hospital-materialflow/
entity schema
business rules
column mappings
human language
Self-contained. Versioned. Declarative.
The engine discovers and loads it via a path variable.
Swap the directory → swap the domain.
The patterns are universal
- Balance probes — compare two aggregates. Usage vs billing in hospitals. Received vs sold in retail. Ordered vs delivered in construction.
- Duplicate detection — same shape everywhere. Duplicate billings, duplicate invoices, duplicate shipments.
- Trend analysis — rolling average drift. Material costs, lead times, defect rates. The math is identical.
- Mandatory item — “this entity must have that child.” Implant with hip replacement. Fire extinguisher with building inspection. Safety sheet with chemical batch.
- Taxonomy hierarchies — cost centres, product categories, regional structures. Same closure table, different labels.
AI as Subject Matter Expert
The framework is the engineering. AI is the domain knowledge.
nuMetrix was built with AI
as the domain expert.
No hospital consulting engagement. No six-month discovery phase.
AI brought the SME knowledge. The framework made it actionable.
New domain = new conversation.
Same framework.
engine
domain knowledge
contracts + probes + i18n
Instance
To enter retail: ask AI about SAP Retail schemas, shrinkage patterns,
planogram compliance, margin erosion — generate the domain pack.
To enter pharma: ask AI about batch records, LIMS formats,
yield calculations, GMP compliance — generate the domain pack.
The framework stays. The expertise is injected.
Each domain pack makes AI smarter
for the next one.
- Hospital deployment reveals that balance probes need interpretation rules — DRG inpatient vs outpatient. The engine gains the interpretation layer.
- Retail deployment reveals that shrinkage probes need seasonal adjustment. The DSL gains a
seasonalmodifier. All domains benefit. - Each domain's calibrated thresholds inform the next. “What does normal look like?” gets answered by data, not guesswork.
- AI accumulates cross-domain patterns. The framework gets better at every domain because it's been to others.
Where jinflow Fits
Six industries. Same engine. Different domain packs.
Material/resource flows + financial reconciliation
Every domain has the same shape
different column names
validated entities
reconciliation + anomalies
business language
Multiple source systems → canonical model → financial/operational reconciliation
→ diagnostic probes → management-level hypotheses.
The strongest fit is anywhere you see this shape.
The entity names change. The architecture doesn't.
Same probe types. Different vocabulary.
| Probe Type | Hospital (nuMetrix) | Retail (jinflow) |
|---|---|---|
| balance | Usage value vs billed amount | Received qty vs (sold + on hand) |
| mandatory_item | Hip replacement → implant | Store type → core assortment |
| trend | Material cost drift per month | Margin erosion over rolling window |
| distribution_outlier | DRG cost outlier per case | Return rate anomaly per product |
| assessment | Case financial integrity | Store health score |
The probe compiler generates identical SQL structures.
Only the entity names and thresholds change.
What Cannot Be Copied
The engine is reproducible. The domain packs are not.
Each domain pack encodes
knowledge that accumulates.
- Regulatory knowledge. Swiss KVG. BetmG. MiGEL. GMP. Food safety. Each domain has its legal landscape. The domain pack encodes it.
- Calibrated thresholds. SZO's I/O coefficient of 0.39 tells you what “normal” looks like at a Swiss regional hospital. You can't guess this. You earn it from data.
- Interpretation rules. “A 40% billing delta on a DRG inpatient case is expected. On an outpatient case, it's CHF 2,500 at risk.” The difference between noise and signal.
- Source-system expertise. OPALE's 5-digit mandate prefix. SAP BWART 301 = TRANSFER. Navision's “Negative Adjmt.” = ISSUE. Earned through ingestion, not documentation.
Open engine. Expert domain packs.
Open or source-available.
Drives adoption and trust.
The platform. Free to evaluate.
regulatory context, calibrated thresholds.
Subscription per tenant.
The expertise. The revenue.
a domain pack for a new industry.
AI-accelerated. Weeks, not months.
The growth engine.
The framework
that learns every domain
it enters.
nuMetrix proved it works for hospitals.
The engine is domain-agnostic. The domain packs are pluggable.
AI brings the expertise. Each deployment makes the next one faster.
One framework. Many domains. Infinite expertise.