// Sector
Critical Infrastructure
OT/ICS risk depends on assets, controls, networks, conditions, and business impact - but the teams that own each piece rarely share a picture.
Why critical infrastructure decisions are hard to make well.
Risk in critical infrastructure is a joint function of four things that are almost never held by the same team: what assets exist and how they are configured, how they are connected, what is known to be wrong with them, and what happens to the service if they stop. Security owns the vulnerability data. Operations owns the process consequence. Engineering owns the configuration. The result is a remediation queue sorted by severity score rather than by consequence, which is how organizations spend a quarter patching things that could not have hurt them.
Ridgeline AI assembles the joint picture. OT and ICS asset inventories, network topology, vulnerability and advisory feeds, operating procedures, and service impact models are bound into one graph, so criticality is derived rather than asserted. Remediation is sequenced by what the loss of a given function would actually do to the service, and the reasoning behind that sequence is inspectable by the people who have to sign the change.
The same model shortens response. During an incident, the question is not only what is affected but what depends on it, which procedure applies, who is qualified, and what the safe fallback state is. Holding that in a model rather than in binders means the answer arrives while it is still useful.
Nothing acts on its own authority. Actions with physical consequence are bounded by policy, require the right human authorization, and are recorded end to end - from the signal that raised them to the signature that approved them. That record is what makes the program defensible to a regulator and to your own board.
- OT/ICS asset inventories
- Network data
- Vulnerability data
- Procedures
- Impact models
- Asset criticality
- Remediation sequencing
- Response planning
Mission applications that fit this operation.
// Critical Infrastructure
OT Risk & Resilience Center
An operating picture for OT/ICS risk - asset criticality, controls, network exposure, and business impact in one governed view.
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// Industrial Operations
Maintenance Intelligence
Connect work orders, sensor data, inspections, parts, and asset history into one decision layer - so maintenance teams act before things fail, not after.
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What operators ask about critical infrastructure.
Does Ridgeline AI write to control systems?
Only where a customer explicitly authorizes it, inside policy bounds, with human authorization and a full audit record. The default posture is read and recommend; write authority is granted deliberately, per action class.
How is criticality determined?
It is derived from the service impact model rather than taken from a generic severity score - what the asset does, what depends on it, and what the operational consequence of its loss would be.
Can this coexist with existing OT security tooling?
Yes. Ridgeline AI consumes inventory, network, and vulnerability data from the tools you already run and builds the prioritization and response layer above them.