Reo agents run operational workflows across the software you already use — gathering context, taking action, routing approvals, and bringing your team the exceptions.
Software holds the records and executes the transactions. The rest still needs a person: interpreting what came in, gathering context, applying policy, reconciling records, deciding the next step, acting, and following through.
That work rarely fits a fixed rules engine — inputs are unstructured, paths vary, decisions depend on context. Reo agents take it on within clear boundaries, and bring people in only where the case genuinely requires them.
Take one familiar example — an invoice that doesn't match its purchase order.
Cases that cross a boundary — authority, policy, risk, uncertainty — go to your team with the context already assembled.
Agents handle the work. Your people handle the boundaries.
Pick a function. The workflow changes; the shape underneath doesn't — interpret what arrives, gather the context, decide within policy, act across your systems, verify the outcome.
How an invoice exception moves when an agent owns it, end to end. The same pattern runs across AP, AR, close readiness, and reporting — on the ERP and expense systems you already have.
BRING US ONE OF YOURS →Eligible work reaches the intended outcome — and the workflow is checked against it.
People stop shepherding every routine step — the touches that remain are the ones that matter.
Work keeps moving instead of waiting for someone to pick it up.
Eligible exceptions get worked; the ones that need your team arrive with the case assembled.
The operation completes more work without review effort growing at the same rate.
Every workflow Reo agents run starts with an explicit definition of success. The dimensions depend on the workflow:
We measure useful work completed — not how much AI was used.
We evaluate the workflow, not just the model output.
Every deployment is designed around four questions enterprise teams ask.
We use deterministic automation where predictability wins, agents where context and adaptive decisions add value, and people where judgment, authority, or risk requires them.
"Does it understand enough about our operation?"
Reo agents assemble the context behind the work — records, policies, SOPs, workflow history — so decisions reflect how your business actually runs — the right context for the decision, not the maximum context.
"Can it actually do the work?"
Where authorized, Reo agents act through your systems — update records, send requests, write results back — and carry the work through to completion. They don't advise from the sidelines; they do the permitted work.
"Can we define what it's allowed to do?"
You set the boundaries. We design deployments around least-privilege access, explicit permissions, approval requirements, and escalation rules.
"How do we know it worked?"
Deployments are designed so actions, approvals, and escalations are observable — and workflows are evaluated against their definition of done, business rules, and final system state.
Reo agents work through the systems your operation already relies on — reading state, taking authorized actions, writing results back. The stack is their context and their tools, never a new system of record.
We configure a Reo agent system around the workflow: instructions, context, tools, decision boundaries, permissions, approvals, escalation, and evaluations — defined before anything runs.
Verified outcomes, corrections, and decisions become context for future runs — broadening what the agents handle and earning the system more responsibility where justified.
A working session on one workflow: how it runs today, which systems it touches, whether an agent is honestly the right tool, and what a deployment would involve.
Meaningful volume, several systems, clear boundaries, a measurable outcome — and work that still needs a person to interpret, decide, and follow through on every case. High-judgment, low-volume, or poorly defined work is a bad place to start — and we'll say so.
They take on defined operational work: interpret what comes in, gather the relevant context, apply your policies, determine the next permitted step, act through your systems, handle eligible exceptions, and verify the outcome — all inside the authority you define.
It depends on the workflow's complexity and the systems involved. Discovery ends with a scoped plan and timeline for your specific workflow — a real number, not a marketing one.
It depends on the workflow: approvals your policy mandates, high-consequence decisions, cases outside the agent's authority, and situations where uncertainty exceeds defined boundaries. Judgment you intentionally keep human stays human.
Within its boundaries, it can gather more context, take another permitted action, or follow an approved exception path. When the case remains outside its authority or operating boundary, it escalates — with the relevant context assembled.
Enough to teach us the workflow: context sessions during discovery and design, sign-offs at decision points, and your approvers once live. We handle the build, integration, and operation.
Reo agents are designed to work across the systems where the workflow already happens, using available integrations and interfaces. If tooling should change, that's a conversation — not a prerequisite.
Every deployment is configured around your specific workflow — your context, rules, permissions, approvals, and definition of done. There is no generic template you have to adapt to.
Only what you authorize. We design access around least privilege, explicit permissions, and approval boundaries. Agents can only take actions authorized for the workflow.
Agents operate inside the permissions and security policies you already enforce, and deployments are designed so the workflow is traceable end to end — what the agent did, what context it used, what was approved, and what escalated.
Scoped per engagement after discovery, based on the workflow's complexity and the systems involved.
