Industries

How real industries break, link by link.

One engine, any industry. Below are five: how each one quietly breaks, the chain that carries a small event into an expensive ending, and what that ending costs in the real world. Every figure is a real, publicly reported fact, not a Vyom result. They show the pattern Vyom is built to catch, simulate, and act on before it lands.

ConstructionRain → cash
ManufacturingSupplier → margin
SaaSAdoption → renewal
LogisticsDelay → penalty
HealthcareNo-show → revenue
Pick one to refocus the lens ↓
Pick an industry

The same shape, in every one.

A dependency slips somewhere upstream. It stays quiet because no single team can see the whole chain. By the time it shows up in the numbers, it already happened weeks ago and costs far more to fix. Pick an industry and watch the chain run.

5
industries below · one engine runs all of them

The chain
What it costs, in the real world
What Vyom tracks here
Case study · a real, documented incident
Real, publicly reported facts about each industry, with sources named. Not Vyom results. Vyom is pre-seed with zero live deployments. Everything the product itself does is built and verified on reality-grade synthetic companies with known ground truth. These are the patterns that verification is measured against.
One engine, not five products

Different vocabulary.The same math.

Every industry above loads different variables, connectors and signals, and gets the same product on top. The model is the engine underneath; what you work with is the whole platform and a workforce of agents running from it.

Nothing in the runtime knows what industry it is looking at. If a line of code ever branched on the industry, that would be a bug we would remove.

01
Ingests
Events arrive from the systems you already run.
02
Builds the model
The causal model of how your company works.
03
Simulates
A fix, before anyone commits to it.
04
Surfaces
To each person it affects, in their own terms.
05
Acts
Through the systems you already run.
06
Captures
Why the call was made, so it is never lost.
07
Sharpens
Every time. The model gets better as it runs.
if industry == "construction". A line like this never exists in the runtime. Industry lives in configuration, never in code.

A company that fits no template can still be reasoned about: describe it in plain English and the engine spins up a synthetic model to explore in seconds. Onboarding a real company is data-first, built from its own systems.

Walk the live model → See a worked example end to end →
One engine, the same math

The list keeps going.

The five above are where we've gone deepest. The engine reads any operations-heavy business the same way: find the wiring, watch it, and catch the chain before it lands. A few more, one line each.

Utility & energy
heatwave → grid load → capacity strain → price spike
Pharma & biotech
raw-material impurity → batch yield → the reject-or-risk call
Retail & e-commerce
a supplier stockout → an empty shelf → lost sales before the reorder
Hotels & hospitality
a group cancellation → occupancy → rate strategy → RevPAR
Food & beverage
a cold-chain excursion → spoilage → recall exposure
Banking & lending
delinquency rising in a cohort → provisioning → the capital ratio
Insurance
loss-ratio drift in a book → reserve adequacy → underwriting
Professional services
utilization slipping → realization → cash runway

Your industry isn't on the list? It runs the same.

The engine is industry-agnostic by construction. Tell us about your business and we’ll build your model from your systems, with you.

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