The opportunity
Agents are moving out of pilots and into the work itself.
One agent is a demonstration. Hundreds is an operating model, not because the agents cannot do the work, but because at that scale they draw on the same systems, act on the same records at the same moment, and commit real spend with every run. This is where most enterprise AI programmes stall.
OrionEQ is the layer they all run on. Work is sequenced so agents hand off rather than collide, every action is written to a record you can defend, and what one agent learns remains available to the next. Scale becomes a decision you make, not a risk you absorb.
Orchestration
Agents hand off work, they don't collide over it
Set the priorities once and let the platform hold the line. Work flows in the right order, and no two agents end up acting on the same thing at the same moment.
See orchestration in your agentsDone
Running
Waiting
Sets the route
Waits
Governance
Every action, accounted for
See what your agents did, stop one when you need to, and stand behind the record.
See a live audit trail| Agent | Status | Spend | Last action |
|---|---|---|---|
| Three-Way Match | Active Last run 09:42 | $186 / $500 | Posted INV-4821 09:42:07 · agent |
| Order Exception Router | Active Last run 09:18 | $91 / $300 | Rerouted SH-204 09:18:22 · agent |
| Freight Audit | Budget alert 80% of limit | $164 / $200 | Held SH-204 09:38:12 · agent |
| SAP IDoc Listener | Active Awaiting review | $47 / $400 | Held INV-5104 09:11:08 · system |
| Bank Reconciliation | Budget stop Skipped until raised | $250 / $250 | Limit reached 09:31:40 · system |
| Access Recertification | Paused Stopped by admin | $18 / $100 | Kill switch enabled 09:24:03 · m.okonkwo |
Memory
What one agent learns, the others can use
Your agents improve together instead of each starting from zero, and when someone corrects one of them, the correction holds.
See memory in actionSecurity
Isolated by default, not by configuration
Your data stays yours. It is kept apart at the infrastructure level, reached only through your own identity provider, and never used to train a model.
Talk to our security teamBenefits for your enterprise
Agents at scale, on terms you control
What changes when every agent runs on one layer.
Scale with confidence
Adding the next hundred agents is a decision, not a risk you absorb.
Stand behind every action
A record ready for audit, the board, and the teams your agents touch.
Risk inside your limits
No collisions, no runaway spend, and a stop that actually stops.
Learning that compounds
What one agent learns serves the next, and corrections hold.