Governed AI for complex, distributed operations.
For operators, network infrastructure and communications providers. Agents work across distributed systems inside policy, with customer and network data under your control.
- Customer and network data under your control
- Agents inside policy across systems
- Audit trail for every action
Network incident triage
Context first, change only with approval.
Problem: alarms and tickets arrive from many systems at once. Agent: correlates approved sources and proposes likely causes and next steps. Control: read-only access to network systems; configuration changes require engineer approval. Outcome: engineers start from assembled context, and every suggestion is recorded.
- Read-only network access
- Engineer approval for changes
- Suggestions and decisions recorded
Customer service agents
Resolve within limits, escalate the rest.
Problem: support teams handle high volumes across billing, service and device issues. Agent: answers and acts on approved account data. Control: it can only reach the data and actions policy allows, and refunds or plan changes above a threshold need approval. Outcome: consistent handling with a record of each action.
- Scoped account data access
- Approval above set thresholds
- Every action recorded
Fraud and abuse review
Triage with evidence attached.
Problem: suspected fraud cases need evidence assembled across systems. Agent: gathers it and drafts a recommendation. Control: personal data handling follows classification rules, and blocking or closing an account needs a person. Outcome: reviewers decide on evidence, not on gathering it.
- Data classification enforced
- Human decision for account actions
- Evidence retained
Operational knowledge
Runbooks answered from your own documents.
Problem: runbooks and vendor documentation are scattered. Agent: answers from them through Cortex. Control: access rights enforced, sources cited. Outcome: faster resolution with queries that can be audited.
- Access rights enforced
- Sources cited
- Queries auditable
Data and sovereignty considerations
Compliance-by-design: Swfte provides the technical controls, governance mechanisms and evidence needed to deploy AI within your applicable regulatory, security and policy requirements. The exact posture depends on your use case, jurisdiction, deployment and configuration. See the trust page for what is true today.
Customer data control
Designed so you decide where subscriber and network data is processed and who can reach it.
Deploy across your estate
Designed for private, dedicated or hybrid deployment across your infrastructure. Scoped with you.
Supply-chain visibility
See the models, vendors and dependencies behind each agent.
Evidence across systems
Traceability from data to model to agent to decision to action.
Frequently asked questions
Only if you grant that permission. Agents default to least privilege, and configuration changes can require human approval.
Customer data is stored in AWS Ireland today. The platform is designed to let you choose private, dedicated or hybrid deployment and your data location. Talk to our team to scope it.
Compliance-by-design: Swfte provides the technical controls, governance mechanisms and evidence needed to deploy AI within your applicable requirements. The exact posture depends on your use case, jurisdiction, deployment and configuration.
One platform, built for control
Sovereignty
Control over where and how AI runs, and over the data, models and agents inside it.
Governance
Runtime policy, human approval and an audit trail across every layer.
Governed agents
Agents that act within limits you set, and leave evidence of what they did.
Swfte Connect
The model gateway and routing layer, designed to run in your own cloud, VPC or data centre.
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