An agent you would let near an invoice.
Automation that handles the exception instead of forwarding it. Under human oversight, with a confidence threshold, an escalation path and an audit trail behind every action it takes.
Most automation in an established business handles the easy eighty percent and hands the rest to a person. That is not a criticism of the design. Static rules can only cover cases someone anticipated, and the cases nobody anticipated are exactly the ones that arrive.
The trouble is that the remaining twenty percent is where the cost sits. It is the slow, manual, expensive part of the workflow, and it is also the part where being wrong is expensive. Which is why the automation was written conservatively in the first place.
Agents change what is reachable in that twenty percent. They also change what is at risk, which is the part of the conversation most vendors skip.
Who this is for
Operations, finance and shared-service teams inside companies where a workflow already runs at volume: invoices, documents, claims, onboarding packets, exception queues. You have automation in place. It works. It stops at the same wall every time, and headcount is what you have been throwing at the far side of that wall.
What we build
Agents that complete tasks under human oversight, inside workflows we understand well enough to know where the oversight has to sit.
The work behind this is not new for us. Automated invoice processing. Document extraction and workflow automation. Automated integrations into third-party applications including Salesforce and Google Ad Manager. Business process assessment, standard operating procedure creation, automation centre-of-excellence setup, and the return-on-investment modelling that decides whether any of it is worth doing.
We have run this across finance, banking, insurance and investment planning, internet media and advertising, automotive, oil and gas, transportation and logistics, healthcare, property management, retail and manufacturing.
What has changed is the class of task that is now automatable. What has not changed is that an automated action still has to be correct, attributable and reversible.
The oversight architecture
This is the part that decides whether an agent belongs in your operation. We design it before we design the agent.
Confidence thresholds.
Every decision the agent makes carries a score. Below the line, it goes to a person. The line is set by what an error costs in that specific workflow, not by what produces an impressive demo. A high-value payment run and a low-value document reclassification do not get the same threshold.
Escalation paths.
When the agent hands off, the person receiving it gets the case, the agent’s reasoning, and the specific thing it was unsure about. An escalation that arrives as a bare exception has moved the work without reducing it.
Audit trails.
Every action, the inputs it acted on, and the derivation. Reproducible after the fact. If you cannot show an auditor why the agent did what it did, the agent should not have done it.
Reversibility by design.
Where the choice exists, we prefer the action that can be undone. An agent that prepares and a human who approves is a better architecture than an agent that sends, and it is usually only one click apart in the user experience.
Scope limits.
Agents get the narrowest set of permissions that lets them finish the job. Broad credentials are how a contained error becomes an incident.
Measurement.
You need to know the escalation rate, whether it is falling, and where the agent is quietly wrong, not loudly stuck. An automation programme without this instrumentation is running on faith.
What we will tell you not to automate
Some workflows should stay manual, and some should stay on static rules.
If a decision has to be defended to a regulator, a deterministic rule that can be produced on request usually beats an agent that was probably right. If a workflow runs eleven times a year, the automation will cost more than the work. If the process is about to change, automating the current version buys you a migration.
We would rather say this during the assessment than eight weeks into a build.
How the engagement runs
The AI Modernization Assessment comes first. Two weeks, $5,000. We work with the people who actually run the workflow, including whoever handles the exceptions, because they know things the process documentation does not contain.
You get a prioritized roadmap with effort and cost ranges, and a written list of the workflows where an agent would add risk without adding value. Then the highest-value item becomes a scoped pilot.
Book the assessment
Two weeks, $5,000. We work with the people who run the workflow, and we come back with a roadmap and a list of what an agent should not touch.
Book the assessment