human-led by design
Autonomy you control.
Trust you can verify.
We build, operate, and continuously improve our Agentic Order Management System with one clear priority: protecting your data and ensuring the reliability your business depends on. fulfillmenttools agents act within boundaries you define.
Agents act within boundaries
Escalation below confidence threshold
Audit trail for every decision
The governance principle
Agentic where it adds value, deterministic where it doesn't
Not every OMS decision should be agentic. High-volume, well-structured decisions are better served by deterministic rules: predictable, traceable, cheap to run, easy to audit.
Our rules engine stays the right tool for those. We reserve agents for decisions that are context-rich, multi-objective, and variable — where fixed rules force compromises or manual rework.
Every agent needs a clear goal and a measurable contribution.
If we can't define both, we don't build it.
escalation ladder
Governance by design, not by checklist
Set confidences threshold at which an agent acts alone. Below it, the agent escalates. Above it, it acts and reports. Thresholds are configurable per customer, use case, and agent.
First
Notify
The default within scope. Agents act, resolves issues, and informs people and systems that need to know. No waiting, no bottleneck.
Second
Approve
Above a defined threshold, the agent prepares the decision, presents the options and trade-offs, and wait for human confirmation.
Third
Co-decide
The agent do not act alone. It surfaces the pattern, proposes responses, and make decicions together with teams.
transparency
Every AI decision is visible and verified
Retail and B2B order management runs on contracts, payments, and trust. Every AI agent decision needs to hold up to scrutiny.
Explainable
After making a decision, the agent can articulate why it decided the way it did: which options it evaluated, which criteria tipped the balance, which data it used.
Traceable
Every action leaves an audit trail — which agent, which version, with what input, with what outcome. Fully reconstructible weeks later, so you can answer compliance questions or investigate disputes long after the decision was made.
Reversible
Actions can be undone or corrected through compensation, rollback, or override, wherever operationally possible. Terminal actions, like a dispatched carrier pickup, need higher confidence or human confirmation.
Evolution stages
No agent starts fully autonomous. Stages progress as trust, data quality, and guardrails mature. Every customer, use case, and agent can sit at a different stage at any time.
Understand
The agent suggests a course of action, but humans make every final decision before anything happens.
Human involvement
- Every decision
Configure
The agent acts on its own, but humans review and approve each step before it's executed.
Human involvement
- Every action
Optimize
The agent acts independently within set limits, and humans only step in when exceptions occur.
Human involvement
- Exception-based
Execute
The agent acts fully independently within policy, while humans focus on audit and policy oversight.
Human involvement
- Audit and policy
Reference case
Governance in action: The Order Monitoring Agent
A shortpick threatens a delivery promise. The agent checks fulfillment probability, simulates alternatives — reroute, substitution, split, carrier switch — and weighs sunk cost against reroute cost against likely customer acceptance. It acts on the strongest option.
In scope
The agent resolves the shortpick risk and notifies your team thus no bottleneck arises.
Above threshold
The agent prepares the decision and options, then waits for your approval.
Systemic pattern
The agent prepares the decision and options, and then waits for your approval.
Proactive by default, escalate by design
That's what your client advocate looks like under governance.
Proactive within scope and escalating by design.