Give technical teams a shared development environment, a deployment runtime and agent controls.
Choose the products and model endpoints that fit your requirements.
The problem
Developers need tools and data access. Platform teams need repeatable deployment. Security teams need to understand model destinations, permissions and activity.
Calliope AI provides products for these tasks, with implementation and support available for the parts your team needs help operating.
Maintain a shared approach to environments, model access and credentials across projects.
Give developers a configured environment without repeating the same provisioning work.
Keep workspace access records and add agent activity and policy evidence through Zentinelle AI.
Unapproved tools spreading, each with a different security posture and its own credentials.
The solution
Run Workbench and workloads in your chosen environment. Connect approved model endpoints and data sources, using local inference where external model traffic is prohibited.
Calliope AI Workbench gives technical teams a shared development environment with first-party tools and selected open-source integrations.
Inside the Workbench
AI Lab adds AI assistance to JupyterLab. Work with approved data sources and model endpoints for queries, code and analysis.
AI IDE and agents support planning, code changes and review with approved model providers. Configure permissions and review requirements for each workflow.
Zentinelle AI records activity and evaluates policy through supported integrations. Coverage depends on the connected agents and enforcement points.
Workloads run in your account. Model requests go to approved endpoints.
AWS is supported today. Other backends are in progress; migration effort depends on the workload and target environment.
License Workbench seats and add runtime, policy or support where needed.
Configure model access, tool permissions, budgets and rate limits through supported enforcement points.
Not 18-month build cycles.
The run layer puts the whole stack in your account — runs on AWS today, built to port. BYOC and VPC peering, with more backends on the roadmap.
Explore deployment →
Zentinelle AI adds agent observability, policy evaluation and evidence for review. Compliance mappings do not confer certification.
See governance →
Secure wraps all of it — private deployment and real-time enforcement, in your cloud or colo, inside your perimeter, under your security controls.
Use cases
Build it once, on infrastructure you own.
Autonomous agents that plan and execute, inside your perimeter.
Ask questions using approved data sources and model endpoints.
Internal assistants with configured access and optional agent policy.
Connect workflows and retain activity through supported integrations.
Free download
The guide we use with enterprise teams: the BROCS reference architecture (Workbench + Astrolift + Zentinelle) for self-hosting AI in your VPC, a security & GRC checklist, and the path from zero to governed production. No form, no gate.
Explore the blueprint → Download the PDF
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Discuss your workloads, model access and deployment requirements.
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