Decisions agentic orchestration platform—engineered around an enterprise rules engine—helps agents take action safely, consistently, and reliably across processes and systems.
Agents relying on prompts instead of policy deliver different outcomes for the same request. No consistency. No defensibility.
Regulators don't accept "the LLM decided" as an answer. Without deterministic rules, your audit trail has gaps you can't close.
Every team is building agents. No one is coordinating them. Logic is scattered, duplicated, and impossible to version or roll back.
Decisions brings together orchestration and deterministic control. The rules engine is the deterministic layer that keeps agentic work compliant and predictable.
Define exactly what each agent is authorized to do—and what it isn't. Statement rules, truth tables, and matrix rules enforce boundaries that no prompt injection or model drift can override.
Let AI agents handle the ambiguity—reasoning over unstructured data, interpreting context, adapting in real time. But lock the final decision to your rules.
“There hasn't been a single project I haven't been able to tackle while using Decisions. It has vastly helped improve the efficiency of our day-to-day processes. Other BPM/no-code software seems to do a lot, but Decisions truly handles everything I throw at it.”
As AI agents move from recommendations to action, governance becomes critical. Learn why rules engines are emerging as the control plane for safe, scalable enterprise AI.
Govern agent behavior with reusable, versioned logic business and IT teams can understand.
Orchestrate agents, models, APIs, tools, apps, data, and workflows through one governed enterprise platform.
Monitor agentic processes, surface exceptions, and improve performance with process intelligence
Agentic orchestration is the coordination of AI agents, human tasks, business rules, and enterprise systems within a governed framework—so that autonomous agents can operate reliably, compliantly, and transparently across end-to-end business processes.
Decisions is built around a native rules engine that processes billions of evaluations per hour. Every agent action is governed by the same deterministic rules your enterprise already relies on—not just visual workflows or prompt-based instructions.
Build agentic processes with the orchestration, rules, and visibility needed to move from AI experiments to governed enterprise execution.
Agents finish tasks with no governed way to route results, escalate, or trigger what's next. Critical work falls through the cracks.
Redundant agent calls, uncontrolled API usage, and constant rework drive costs up—while trust in the results stays low.
Agents can act before the right person has a chance to review, approve, or intervene. By the time an issue surfaces, the action is already complete and harder to unwind.
Shadow-test agent behavior against your rules before anything goes live. A/B test rule variations. Roll back instantly if outcomes drift. Every change is versioned, every result auditable.
Use the agents, models, and systems that fit your business without rebuilding core processes.
Track the rules, inputs, outputs, handoffs, and approvals behind every agent-driven outcome.
Set approval points, escalation paths, and exception handling so agents can move work forward without acting beyond defined business boundaries.
The rules engine acts as the governance control plane. It defines what agents can and cannot do, enforces compliance boundaries, triggers escalations, validates outputs, and ensures every decision is consistent, auditable, and aligned with your business policies.
Yes. Decisions is model-agnostic and integrates with any LLM provider, agent framework, or custom-built AI service through REST APIs, SOAP, .NET assemblies, and message queues. You control the intelligence; Decisions governs the orchestration.
No. The platform supports the full spectrum—from rules-driven automation with no AI, to hybrid workflows that blend deterministic rules with AI-powered agents. You can start with rule-based automation and layer in agentic capabilities as your organization matures.
Rules define confidence thresholds and escalation triggers. When an agent’s output falls outside acceptable parameters, the platform automatically routes work to the right human reviewer with full context—then resumes the orchestration once the human decides.
