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AssureLens - Agentic AI for Energy
AssureLens overview

Trust & security

Data Security

Security requirements belong in the architecture and acceptance criteria from the start. This summary describes how AssureLens approaches the protection of client and operational data.

Last updated: 22 September 2026

Deployment on your terms

AssureLens can be deployed on any public cloud or on your own premises. Data residency, network boundaries, model hosting and support responsibilities are agreed with your IT and security teams during discovery.

Access & isolation

  • Authentication, project roles and authorised sources are agreed up front.
  • Client data is isolated, and permissions apply to records and their derived outputs.
  • Only authorised reviewers can finalise findings and retain sign-off.

Data protection

  • Encryption in transit and at rest, using industry-standard mechanisms.
  • Defined retention, deletion and residency, agreed with your teams.
  • Permitted model processing is scoped explicitly - client project data is not used to train shared models.

Operational separation

The reference approach reads approved rig-system data and processes it on shore. It preserves a read-only boundary and keeps decision support distinct from operational control and human sign-off.

Audit & traceability

We record source lineage, transformations, expert review and release changes, and define approval and escalation routes so teams can inspect how a finding was formed.

Human accountability

AI agents organise the evidence; subject matter experts review the findings; your team owns the decisions. Reviewers, decision owners and approval points are defined for every engagement.

Responsible disclosure

If you believe you have found a security issue, please contact us at hello@swarmlens.com so we can investigate promptly.

Specific controls are specified and verified for the selected deployment. This page describes our approach and does not assert a particular certification.