Agentic AI Workforces

Run your agents
like a department.

We build agent workflows and run them on Agent Mission Control, where your people manage every agent, what it costs and what it returns.

Where this fitsThe 4-phase transformationSee the model →
  1. 01Human-led innovation
  2. 02Skill codification
  3. 03Agent-led workflows
  4. 04Agentic departments

What’s not working

AI assistants
aren’t a workforce.

We’re all faster. The process isn’t.

Faster people, same workflow

Your people get quicker at their own tasks, but nothing connects them. Every handoff still waits on a person to notice it and carry it to the next step.

Every new hire means another license.

Cost that never inverts

Per-seat licensing scales with headcount, not throughput. The unit economics don’t change, so the gains stay anecdotal.

It only runs if her laptop is open.

AI no one can see

The automations people build run as them, on their own machines and under their own limits. When someone is out or leaves, the work stops, and no one can see what AI is doing across the company.

What is an agentic department?

Agents organized
like a team.

The department has a budget, performance metrics and a person who runs it. The agents are operated, not just deployed.

You delegate to agents the way you delegate to people: with oversight, accountability and a way to escalate.

Why we built Agent Mission Control

Every capability traces
back to a problem.

The problem we kept hitting What Agent Mission Control does
Finance teams couldn’t get invoice exceptions out of agent queues fast enoughRoutes every exception to a person, on an SLA
CFOs wouldn’t approve more spend without defensible mathROI per workflow, traced to billing and the run log
Ops managers couldn’t tell which workflows were earning their placeDepartment-level views of cost and return

Agent Mission Control

The business operations center
for your agentic workforce.

Our product for running agents. Manage. Measure. Govern. The same accountability you expect from any other department. Built by Cay Digital, and we run our own business on it.

Manage

One queue for every agent, task and human intervention.

Agents ask before they guess: a person approves, with an SLA on every request.

Measure

Cost per unit of work: token spend plus the human time to supervise it.

Department budgets with hard caps. Every dollar traces to Azure billing and the run log, with ROI per workflow.

Govern

Rubrics with pass/fail on every run.

Every agent knows when it may act and when it must raise a hand. Failures are attested, and every approval and override is on the record.

How it works

One workflow at a time.
Until the department runs on it.

  1. Pick the workflow

    Start from your catalog: the work that costs the most time and has a clear owner.

  2. Prove it

    Run it on real work against agreed metrics. A person makes the go/no-go call. First workflow live in weeks, not quarters.

  3. Run it on Agent Mission Control

    Agents do the process, people handle the exceptions, and you see the cost and return of every run.

  4. Add the next one

    Each workflow joins the same view, until the department runs as one team.

The loop: pick a workflow, prove it, run it on Agent Mission Control, add the next one; one workflow at a time PICK PROVE RUN ADD NEXT ONE WORKFLOWAT A TIME

How it is vs. how it’ll be

Assistants vs. an agentic department.

“We rolled out assistants” An agentic department
Where the work happens Human inboxes Agent runtime, end to end
What scales Cost without ROI Per-workflow throughput
How it’s measured Survey satisfaction Cost per completed unit
Failure mode Quiet underuse Logged, traced, fixed

Why it matters

Built for production.
Run on your rules.

Runs in your cloud

Your agents, your data, your identity. Interventions route into Teams, ServiceNow and Salesforce, on an SLA your team is held to.

Human-in-the-loop where it matters

Agents act inside the rules you set; humans own the judgment calls.

Honest about platforms

We’re a Claude Partner Network member and a Microsoft partner. We build on both and tell you which fits.