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RESILIENCE & CONTINUITY

Secure the
Backbone of Society

Grid, network, and fleet each generate torrents of operational data, but IT and OT live in separate worlds — and cloud AI is not allowed anywhere near the OT network. That is the problem we solve: one live operational picture of grid, network, and fleet, with real-time anomaly detection and predictive maintenance — frontier sovereign Data & Agentic AI running in air-gapped environments, so you protect energy grids, transport networks, and digital infrastructure without giving up control.

Book a ConsultationPlatform Capabilities

Grid Resilience

Balance loads and detect faults in real-time across distributed energy resources.

OT/IT Convergence

Unified visibility across legacy SCADA systems and modern cloud analytics.

Built for NIS2

Automated incident reporting and risk management to meet EU cybersecurity directives.

Operational Scenarios

Mission-Critical Applications

Ensuring continuity and safety across vital sectors.

Secure Supply Chain Logistics

Logistics

Challenge

Managing sensitive hardware transport requires real-time coordination, but cloud-based logistics platforms expose location data to foreign entities.

Solution

Sovereign agents monitor IoT sensors on edge devices, re-routing shipments based on threat data and weather, communicating only via encrypted channels.

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Resilient automated logistics that functions intermittently offline and leaks no metadata to third-party providers.

Predictive Infrastructure Maintenance

Public Works

Challenge

Reactive maintenance of roads, bridges, and utilities leads to costly emergency repairs and service disruptions.

Solution

Analytics models process data from IoT sensors and historical reports to predict failures before they happen, scheduling preventative maintenance.

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40% reduction in emergency repair costs and extended lifespan of critical public infrastructure.

Crisis Response Coordination

Emergency Services

Challenge

During natural disasters, fragmented data from various agencies delays critical decision-making and resource allocation.

Solution

A unified command centre powered by AI that aggregates real-time data streams to direct first responders and optimise supply chains.

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Faster response times and more efficient deployment of emergency resources during critical events.

Predictive Grid Maintenance

Energy & Utilities

Challenge

Equipment failures in remote substations cause cascading blackouts and costly emergency repairs.

Solution

Edge AI agents analyse vibration and thermal sensor data locally, predicting component failure weeks in advance without uploading terabytes of raw data.

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40% reduction in unplanned downtime and optimised maintenance schedules.

Energy Security

Smart Grids & Renewables

Give control rooms a live operational picture of the grid. Our platform enables real-time anomaly detection and predictive maintenance while preserving operational isolation in air-gapped environments. An AI-ready data foundation cleans and contextualises decades of SCADA and sensor history into one asset ontology before any model or agent reasons over it.

SCADA Protection

Anomaly detection for legacy industrial protocols.

Load Balancing

AI-driven demand response optimisation.

AI-Ready Data

Decades of SCADA history cleaned and grounded for reliable model training.
Logistics & Transport

Resilient Supply Chains

From maritime ports to rail networks, critical transport infrastructure is the lifeblood of the economy. The AI OS coordinates autonomous agents to optimise flows and secure assets against physical and digital disruption.

  • Port Automation: Coordinate cranes, AGVs, and trucks to minimise turnaround time.
  • Rail Safety: Monitor track integrity and rolling stock health in real-time.
High-speed Train
Regulatory Compliance

NIS2 & Cyber Resilience

Meeting the stringent requirements of the NIS2 Directive is no longer optional. Our platform provides the governance, reporting, and incident response capabilities you need to stay compliant. Scoped, per-agent identity means every AI agent touching OT systems is individually authenticated, least-privilege and fully attributable.

Incident Reporting

Automated generation of incident reports within the 24-hour notification window required by NIS2.

Supply Chain Risk

Assess and monitor the security posture of your digital supply chain and third-party vendors.

Business Continuity

Ensure essential services continue to operate even during a significant cyber incident.
100% European Sovereignty

Your Data, Your AI, Your Control

Deploy the Scrydon platform where it makes sense for you — from air-gapped environments to public cloud — with sovereignty, compliance, and auditability built in.

Air Gapped

  • No external network paths
  • Offline signed updates
  • Strict audit trails

On Premise

  • Runs in your datacenter
  • Identity-integrated & compliant
  • Full operational control

European Cloud

  • EU data residency
  • GDPR-first architecture
  • Managed sovereign services

Confidential Compute

  • TEE-protected workloads
  • Encrypted memory & attestations
  • Secure ML inference

Public Cloud

  • Multi-cloud compatible
  • Policy-driven data controls
  • Hybrid & burst-ready

No data leaves your jurisdiction. No black-box AI. No compromises on control.

This is sovereignty by design.

The platform behind this

What these outcomes actually run on

Everything above is delivered by one platform, designed to keep running when the network does not. For the architects and engineers evaluating it, these are the pieces that matter.

See the full architectureRead the documentation
FAQ

Frequently asked questions

What does sovereign AI for critical infrastructure mean, and why does air-gapped or OT isolation matter?+
Sovereign AI means the entire platform — models, data, identity and audit — runs under your control within European or national boundaries, never exposed to a foreign cloud operator. For critical infrastructure this matters because operational technology (OT) governing grids, water and transport must remain isolated from the public internet to limit the attack surface. Our platform deploys air-gapped on-premises alongside operational systems, so AI delivers value without ever breaching that isolation.
How does the platform support NIS2 and cyber resilience, and is it auditable?+
The platform is built to align with NIS2 obligations around risk management, supply-chain security and incident reporting, though alignment is not a substitute for formal certification. Every action — by humans and AI agents alike — is captured in a tamper-evident audit trail tied to federated identity, giving you full attribution and traceability. Zero-trust controls and confidential computing harden the environment so security posture can be demonstrated to regulators and auditors.
Can we run AI in air-gapped or OT environments alongside our operational systems?+
Yes. The platform is designed to run fully air-gapped, with open-weight models served on-premises via vLLM and no dependency on outbound cloud connectivity. It sits alongside SCADA, historians and other OT systems through controlled, one-way or brokered interfaces that respect existing network segmentation. This lets you apply agentic AI to operational data without introducing new pathways into protected control networks.
How can agentic AI improve grid resilience, renewables integration and resilient supply chains?+
Agentic AI can continuously monitor grid telemetry, forecast demand and renewable output, and propose balancing actions that operators review and approve. Grounded in a shared ontology, agents reason across assets, weather and market signals to anticipate congestion or instability before it cascades. The same approach extends to supply chains, where agents flag single points of failure and surface alternative sourcing to keep critical operations running.
We ran an AI pilot — how do we move to organisation-wide, governed AI across our operations?+
Most operators succeed with a contained pilot but stall when scaling, because production demands governance, identity, security and integration that a proof of concept never needed. Our AI OS provides that organisational foundation: federated identity, zero-trust access, a unifying ontology and full audit, so AI can be rolled out across teams and operations under consistent control. This turns isolated pilots into governed, production-grade infrastructure rather than a patchwork of disconnected tools.
How are identity, attribution and audit handled for AI agents acting on critical systems?+
Every AI agent operates under a verifiable identity through federated identity and zero-trust controls, so its permissions are scoped and enforced just like a human operator's. All actions are logged with who, what and why in an immutable audit trail as part of our AI governance, giving you complete attribution for any agent that reads or acts on critical systems. This ensures accountability and supports forensic review whenever an agent influences an operational decision.
How do we keep operational data protected from the cloud operator?+
The platform supports deployment models from fully air-gapped on-premises through to confidential computing in the cloud, where data stays encrypted even during processing. With confidential compute, workloads run inside hardware-isolated enclaves that the cloud operator cannot inspect, so sensitive operational data is never exposed to the underlying provider. You choose the posture that matches each workload's sensitivity without surrendering control of your data.
Is the platform model-agnostic and able to run open-weight models on-premises to avoid lock-in?+
Yes. The platform is model-agnostic and runs open-weight models on your own infrastructure using vLLM, so you are never tied to a single vendor's API or pricing. You can adopt new models as they emerge, fine-tune on your own data, and keep weights and inference entirely within your sovereign environment. This protects against lock-in and ensures long-term control over the AI that supports your critical operations.
Is our historical SCADA and sensor data actually usable for AI, or does it need cleaning up first?+
Usually not as-is. The platform includes an AI-ready data layer that cleans, contextualises and grounds raw OT and sensor history in the ontology before any model sees it, so agents and predictive models reason over well-described, trustworthy data instead of raw, poorly labelled tag streams. This shortens the path from historical telemetry to a production-ready predictive model.
Can we give an AI agent narrow, auditable access to OT systems without a shared service account?+
Yes. Every agent authenticates under its own federated identity with least-privilege, time-boxed permissions, so an agent authorised to read telemetry can never also write control setpoints unless explicitly granted that scope. Every access is individually attributable rather than hidden behind a shared account, which closes off a major class of risk when agents operate near OT systems.

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