Autonomous Cloud Operations (ACO) for Security by Firemind

Overview Cloud security and operations teams face a familiar problem: manual access, slow incident containment, and configuration drift accumulate faster than headcount can keep pace. Traditional monitoring and ITSM tooling surfaces the noise; it doesn't resolve it.

Firemind Autonomous Cloud Operations (ACO) is an AI-driven service that executes routine cloud operations — monitoring, incident triage, remediation, patching, backups, and standard service requests — as policy-governed, closed-loop "episodes." ACO removes humans from the routine control path while retaining explicit human approval for high-risk actions, so operations teams spend their time on architecture and risk decisions instead of firefighting.

Security & Trust Authorization is checked twice, independently, before any action reaches a customer environment: • Plan time: the planner validates every operation against the permissible-actions catalogue and embeds the result in the plan; high/critical steps cannot proceed without human approval. • Execution time: a guard sits in front of every connector and independently re-checks every tool call, scoped to the tenant, before it reaches a cloud or API. Anything not explicitly allowed is denied; approval-gated or uncatalogued actions pause the episode for a human.

The system fails closed by design: if tenant context is missing, the policy database is unreachable, or a command cannot be parsed, the action is blocked — never allowed by default.

AI data handling Inference runs via Amazon Bedrock (Anthropic Claude) in the customer-selected region. Bedrock does not store prompts or responses and does not use them for model training; no data is shared with any model provider or third party. No business or personal data is collected by default (only infrastructure telemetry) and any incidental data in logs is subject to configurable retention and deletion.

Auditability Every action is recorded in an immutable, end-to-end audit trail using OpenTelemetry (OTEL) distributed tracing. Audit records cannot be updated or deleted and are exportable for compliance reporting, capturing per episode: the AI's decision and reasoning, the remediation proposed, approval or rejection (with approver identity and justification), the execution itself, AssumeRole usage, and any configuration change.