OPERATIONS & ORCHESTRATION
Multiple agents. A clear view of the work.
The Quantivus Operating Platform coordinates AI tasks, model providers and local agents. Operations teams track progress, spot blockers and manage approvals in one place, turning separate activities into a traceable workflow.
- Coordinate
- Assign tasks and agents
- Observe
- See progress and blockers
- Control
- Approvals, cancellation and retries
HOW IT CREATES VALUE
From tasks to manageable operations.
When several agents and model providers are involved, visibility matters. QOP shows who is working on what, where tasks are waiting and which results are available.
One view of work in progress, blockers and results across multiple agents.
Read the process
- Tasks: Start work manually or through configured triggers.
- QOP: Coordinate tasks, responsibilities and execution.
- Agents: Assign suitable roles and capabilities.
- Models & tools: Use configured providers and local tools.
- Operations view: Track status, blockers and results together.
From prompt to managed operation
QOP turns requests into trackable work. Tasks can be queued, assigned to capable providers, streamed while they run, verified at completion and retained in an event history.
- Task creation, assignment and status lifecycle
- Hierarchical TaskFlow structures
- Retry, cancellation and reassignment
- Blocked-task and bottleneck analytics
- Real-time execution updates
- Execution history and audit trail
Use models that fit the task
Connect local or hosted models through a shared management layer. Your team can configure the right provider for each task while keeping track of credentials and operating requirements. Available models depend on the deployment.
- Provider and model configuration
- Model synchronization and task queues
- Streaming response infrastructure
- Local-model operation through Ollama
- Cloud-provider credentials kept per deployment
- Workload routing based on configured capabilities
Coordinate specialists with clear responsibilities
Give agents defined roles, capabilities and context. Complex tasks can be divided into manageable parts and their results brought together. People retain oversight, especially when an action affects other systems or people.
- Specialist roles for different types of work
- Persona management and dynamic skills
- Collaborative discussion workflows
- Knowledge and marketplace surfaces
- Provider and local-agent registration
- Human oversight for consequential actions
Automation with approval boundaries
Autonomy rules can react to cron schedules, events, thresholds or expressions. Sensitive operations pass through approval workflows instead of being silently executed.
- Cron and event-driven triggers
- Threshold and expression evaluation
- Action rules for task creation and operations
- Approval workflows for sensitive changes
- Timezone-aware schedules
- Enable, disable and test controls
MCP and local execution
QOP integrates tools for system, filesystem, Git, containers, databases, office documents, networking and development. Local agents connect enterprise environments to the central platform.
- System operations for Windows, Linux and macOS
- Filesystem, Git, Docker and database tools
- Office document capabilities
- Network and research tools
- .NET and Python development operations
- Local agent, file proxy and scheduler
Spot blockers and take the next step
A central operations view shows tasks, component status and events. Teams can see where work is progressing, where an error occurred or where approval is missing. This helps them diagnose issues, coordinate work and decide what happens next.
- Drag-and-drop architecture topology
- TaskFlow distribution and health views
- Central log and system-component views
- Multi-tenant data context
- JWT, roles, lockout and MFA-capable portal
- Container deployment for platform services
Agent orchestration and IT automation
An LLM gateway organizes access to models; an agent orchestration platform also coordinates tasks, execution and oversight. QOP combines these concerns for IT operations, helping teams follow tasks across providers, local agents and approval steps.
- Coordinate multi-agent tasks and model providers
- Follow execution status, retries and operational events
- Agree on supported integrations and rollout scope before deployment
FAQ
Questions, answered clearly
Scope, deployment and commercial terms are confirmed for your use case.
Is QOP only for local models?
No. It documents both local Ollama operation and several cloud LLM providers through a unified interface.
Can actions require approval?
Yes. Sensitive actions can be routed through approval workflows and autonomy rules can be constrained or disabled.
What does TaskFlow provide?
It tracks stages, distribution, bottlenecks, blocked tasks and health so operators can see where work is waiting or failing.
Is every repository capability automatically production-ready?
No. Availability and operational readiness must be validated for the intended deployment, integrations and security requirements.
How do I choose the right scope?
Start with one use case, the people involved and the evidence you need. In a demo, agree on integrations, access permissions and the operational scope before rollout.
NEXT STEP
Make autonomous operations visible, assignable and governable.
We will identify the first task flow, required providers, approval boundaries and operational evidence for a controlled QOP rollout.