Cloud & OpenTelemetry
Both collectors are designed but not yet built.
Two collectors cover AI activity that no inline sensor can reach: model use inside a cloud platform, and AI systems that already emit GenAI telemetry.
AWS Bedrock ingestion
A Python Lambda in the customer's account, or in Lumen's, reads Bedrock model-invocation logs, CloudTrail and CloudWatch, normalizes each invocation into a Lumen interaction, and ships it for detection.
- Posture: log-only. The interaction already happened by the time the log line exists, so there is no Block. Detection is retroactive, and findings and dashboards are the value.
- Cross-account access uses a read-only role the customer deploys, the same shape as the other Labs services' cloud integrations: no credentials exchanged, an external-id-scoped role assumption.
OpenTelemetry receiver
AI frameworks increasingly emit OTel GenAI semantic conventions, as spans
carrying gen_ai.* attributes for prompts, completions, model and token
counts. The OTel collector receives OTLP, maps GenAI spans onto Lumen interactions,
and runs cloud detection over them.
- Zero code change for systems already instrumented with OTel.
- Observability-grade coverage: Log findings, dashboards and SIEM export, not enforcement.
Where these fit
Use cloud and OTel collectors to close the visibility gap, the platform-side AI use your inline collectors never see. For enforcement, pair them with the SDK or a gateway plugin in the request path.