Private AI for telecom operators
Operators hold some of the most sensitive operational data in any industry — subscriber records, network configurations, interconnect commercial terms. Private AI means getting the benefit of modern models without that data ever leaving your control.
What this replaces
Shadow AI is already here
Prompts, tickets, configs and customer records flow into public LLMs today — invisible to security and irreversible once sent.
Bans don’t work
Prohibiting AI removes visibility while usage continues. The realistic strategy is a sanctioned alternative that is both more useful and fully governed.
Local alone is not governed
A local model still hallucinates, goes stale and leaks across teams. Privacy answers where AI runs — governance answers whether it can be trusted.
What the governed copilot does
Customer-controlled deployment
On-premises, private cloud or fully air-gapped. No vendor cloud, no external account, no telemetry.
Approved models
Model-neutral runtime: open-weight defaults or a customer-provided endpoint behind an adapter layer. No lock-in.
Governed knowledge
The AI answers only from documents your administrators approved, with citations, confidence scores and risk labels.
Verifiable evidence
Tamper-evident audit trails, decision records and exportable evidence for security review and audit.
Under governance, always
- Raw enterprise data egress: zero by design; enforceable at the network boundary in on-prem and air-gapped deployments
- Role-based access enforced in retrieval queries
- Signed, verifiable update path — including offline transfer for air-gapped sites
Output is advisory and decision-support only. The system does not execute operational actions, and refuses to recommend production-changing steps.