For security and risk leaders
Say yes with a boundary you can explain.
Your teams need sanctioned AI. You need an accurate answer for workload location, model destinations, credentials, operator access, policy enforcement, and evidence. Calliope AI makes those decisions architectural instead of leaving them to each tool and user.
The bind
A ban does not create control. It creates a blind spot.
Engineers and analysts will use AI where it helps them work. If the approved path cannot handle sensitive code and data, the demand moves to personal accounts, copied credentials, local tools, and workflows security cannot see.
The answer is a sanctioned operating path. Put the Workbench and workloads in an approved environment, define the model destinations, and add agent-level observability and enforcement where the risk requires it.
What changes in review
The architecture gives each risk a named control point.
Customer-owned workload plane
In BYOC, Workbench sessions, workload compute, and storage run in your AWS account under customer IAM and network policy.
Trust Center →Explicit model destinations
Hosted model requests go directly to approved providers. Require a local or in-boundary endpoint where zero egress is mandatory.
Data protection →Base Workbench controls
SSO, RBAC, and workspace access records give the sanctioned Build environment a common identity and administration layer.
Workbench →Agent-level enforcement
Add Zentinelle AI to observe connected traffic, run 24 implemented policy evaluators, enforce decisions, and preserve evidence.
Zentinelle AI →Inspectable operating cores
The Astrolift AI and Zentinelle AI cores are MIT-licensed. Review the code and self-host before choosing support or services.
Open core →Status without implication
Compliance pages separate mappings, alignment, work in progress, roadmap items, and certifications not held.
Compliance status →Review the real system
Bring the proposed topology, not a generic questionnaire answer.
The same control statement is not correct for every managed, BYOC, on-premises, or isolated deployment. Model choice changes the data flow. Adding Zentinelle AI changes the enforcement and evidence surface. Operator responsibilities change with the support scope.
Calliope AI can work through those specifics with your team: the data-flow diagram, customer and vendor responsibilities, current compliance evidence, DPA, subprocessors, BAA availability, and the controls that remain yours.
- Compliance status · framework by framework. See the current status →
- Data protection · workload, model, and credential flows. Review the controls →
- Document packet · public documents plus the request path for restricted evidence. Open the packet →
Make the approved path the useful path.
Send the questionnaire and the topology you are considering. An engineer will identify what Calliope AI controls, what each model provider receives, and which responsibilities stay with your team.
