AI Orchestration
It’s more than moving data. Decisions orchestration coordinates agents, models, people, and systems under a single control plane, managing state, routing, retries, and approvals while rules govern every step.
Move faster with safer, governed AI use.
Leverage always audit-ready and compliant AI.
Eliminate AI sprawl with centralized control.



Decisions unifies rules, workflow, systems, data, and AI agents into a single deterministic orchestration layer—giving enterprises unprecedented control, visibility, and agility across every part of their operations.
Create, customize, and manage AI agents, including third-party agents, and the workflows that drive them inside a single code-free, drag-and-drop design studio. Swap models freely, prove every outcome, and operate at scale.

Compose agents from governed building blocks without hard-coding and use the LLM model of your choice so you get exactly what you need.

Enable communication between agents to delegate, negotiate, and synchronize tasks.

Run, govern, and observe every agent, model, and workflow through a single command center.

Deploy agents anywhere across the business, including Teams and Slack deployment. Easily drop agents into backend workflows.

Decisions lets you use any model without vendor lock-in and deploy on-premise or in the cloud.
Swap models, keep policy: Change LLMs or scoring models with no rule rewrites; your versioned rules and workflows stay the same.
Explainable outcomes: Every call—model chosen, prompt, outputs, rule path, and action—is captured in decision history.
Prebuilt connectors bridge current systems you rely on, including major platforms, data layers, APIs, and automation tools. All integrations, custom or out-of-the-box.
View a list of existing connections.
Schedule a demo to learn how to move fast and govern every action.
AI orchestration unifies models, agents, rules, workflows, and data into a single control plane so AI behaves predictably and safely across the enterprise. Without orchestration, organizations face inconsistent outputs, ungoverned agents, and fragmented model usage.
A control plane centralizes management of prompts, policies, rules, workflows, and agent behavior. It ensures every model call and agent action follows governance standards, enabling traceability, auditability, and deterministic fallback when model behavior changes.
Yes. The orchestration layer is model-agnostic and supports public, private, open-source, and proprietary models, along with MCP endpoints that connect agents to external tools and data. This allows you to change or upgrade models without rebuilding workflows.
A rules engine enforces compliance, security, and business logic before AI outputs are used. Governance ensures consistent decisioning, prevents uncontrolled agent behavior, and provides full visibility into how AI reaches conclusions.