Use casesCritical infrastructure
AI control plane for critical infrastructure.
Federis provides a governed AI layer for infrastructure operators that need secure model access, protected data boundaries and auditable decision paths across sensitive systems.
Built for telecom, transport, ports, public services, industrial operations and emergency response.
Access, data, model and runtime decisions are constrained by policy.
Operators can inspect the evidence and controls behind AI-assisted outputs.
Secure AI control plane for public services and utilities
Critical infrastructure sectors, such as railways, telecommunications, ports and emergency services, need secure, enterprise-grade generative AI that does not depend on third-party cloud providers. Federis secures infrastructure data, enforces granular access control across tenants and provides transparent audit trails for every operation.
Railway network diagnostics and asset repairs
Field engineers query maintenance logs, track schematics and signalling codes to diagnose line faults. Federis keeps rolling-stock manuals partitioned, so repair summaries do not bleed across incompatible train generations.
Tenant isolation
Data and index collections are segmented in vector stores, which keeps asset lines strictly separate.
Strict grounding
The retrieval fabric makes the model cite the exact manual page and schematic version used in its response.
PII filter
Technician details, location GPS coordinates and security codes are redacted from diagnostic summaries.
Telecom outage diagnostics and network security triage
Network operations centre teams query log streams and topology maps to analyse outages and attack signatures. Federis applies sovereignty routing policies designed to keep raw packet traces and topology maps within national boundaries.
Geofenced routing
The sovereignty engine blocks model lanes outside national borders or in unapproved cloud regions.
Deterministic gating
Analysis tools are restricted to authorised security staff, and every prompt and OPA gate result is logged.
High-throughput lanes
The inference fabric queues and prioritises high-severity incident queries ahead of routine maintenance requests.
Emergency dispatch decision support
Emergency dispatchers query maps, traffic telemetry and utility schematics, such as water main valves or gas line grids, to guide responders. Federis gates access to these high-sensitivity municipal files to prevent malicious exploitation.
Clearance ceiling
Dispatchers cannot query water or gas schematics unless they are responding to a validated emergency incident.
WORM audit vault
Dispatcher identity, OPA decision, retrieved coordinates and response details are recorded in tamper-evident logs.
Local inference lane
Designed to run on local, redundant GPU clusters so service stays available independent of external network connectivity.
Deployment fit
- Designed for multi-tenant, multi-region and restricted-network operating models.
- Keeps external infrastructure components replaceable through policy-driven adapters.
Bring governed AI to critical infrastructure.
Talk to us about your environment. We will walk through the control plane against your workloads, data boundaries and audit requirements.
- Zero data egress
- Any model, any cluster
- WORM audit vault