AI Workforce
The work gets done. Nobody has to do it.
We build AI agents trained on how your business actually runs, and put them to work in the jobs your team should not be spending its day on. They run on your own network, inside your cloud, or entirely outside your walls, sandboxed and scoped tightly enough for regulated work. One agent, or a crew across every department you have. Built and trained in house, from Melville, NY and Boca Raton, FL.
The crew runs on Swell, our own agentic platform, or on Harbor, which is the same platform installed inside your organization.
The Honest Version
Enhance the team you have, or fill a role you never hire.
Both are real uses and we would rather say that plainly than sell you a euphemism. Which one you are buying is a business decision, and it is yours.
Your people stop doing the tedious half.
The most common outcome, and the one we usually recommend first. Senior people are absorbing clerical work almost everywhere, because it has to happen and nobody was hired for it. Agents take the queue underneath your team, and the capacity you get back is real.
- No headcount change
- Faster turnaround on the routine
- Your team moves up the value chain
- The easiest version to get buy-in for
A seat you do not need to fill.
Some companies use this instead of making a hire, or instead of backfilling a role that came open. That is a legitimate use and we will build for it. We will also tell you when a job is a poor candidate, because a badly chosen one costs far more than the salary it saved.
- A vacancy you can leave open
- Scale without a hiring cycle
- Predictable cost per function
- Best on well-defined, repeatable roles
What we will not do is pretend this is only ever additive. If you are weighing an agent against a hire, that is a conversation worth having properly, including the parts that argue for the hire. Judgment, relationships, and anything where being wrong is expensive still belong to people.
Where They Work
Every department has work like this in it.
Agents are trained per workflow, not per job title, so the question is never which department they belong to. It is which task in it is the most repetitive and the least loved.
Nothing here is a template we drop in. Two companies in the same industry run their AP process differently, and the agent that works at one would get the other wrong on its second invoice. Every one is trained on your workflow, your systems, and your exceptions.
Not One Assistant
A crew, not a chatbot in the corner.
There is no cap on how many agents a company runs. The platform was built to operate a crew: agents per workflow, grouped by function, each scoped to its own systems, all reporting into one console your team already knows how to read. Add the next one when the last one has earned it.
Start with the job that is most repetitive and least loved. Widen once it has proven itself.
They also hand work to each other. An intake agent that qualifies a lead can pass it to the one that books the appointment, which passes the paperwork to the one that files it. That is the difference between automating a task and staffing a process.
Scope, Train, Operate
Trained on your business, not on a generic idea of one.
The training is the work. A model that has read the internet knows what an invoice is; it does not know that your second-largest customer sends theirs as a photograph, or which three exceptions your controller wants to see personally.
Scope
We sit with the people doing the work and write down what actually happens, step by step, including the exceptions nobody documented. Then we pick the one job worth starting with.
Train
The agent is trained on your workflow, your systems, your vocabulary, and your rules. It is tested against real cases from your own history until it handles them the way your best person would.
Operate
It goes to work inside the guardrails you set, your team clears the exceptions it flags, and we widen its remit as it earns it. You can add the next agent whenever you want.
We start with one task, not a transformation program. The first agent is chosen because it is provable, not because it is impressive. Once your team trusts it, the second one is a conversation about scope rather than a conversation about whether any of this works.
Where It Runs
Your network, your cloud, or nowhere near either.
The platform is the same in every case. What changes is whose infrastructure it sits on, and that is a decision your rules make rather than one we make for you.
On Premise
Inside your own network, on your own hardware. Nothing leaves the building.
Your Cloud
Installed in your own AWS, Azure, GCP, or Cloudflare account. Your bill, your controls.
Our Cloud, Your Tenant
We host and maintain it, isolated to you, with no data shared across clients.
Fully External
Runs entirely outside your walls and reaches in only through integrations you approve.
An on premise install is not a lesser version. It is the same crew, the same console, and the same training, with the model and the data both staying inside your perimeter. If your rules do not allow anything to leave the building, this is the deployment that exists for you.
Guardrails
An agent that can reach everything is a liability.
However well it behaves. Every one of these is a default rather than an upgrade, because a control you have to ask for is a control somebody eventually forgets to ask for.
Regulated Work
Built for the standard you are held to.
Most of the interesting work in a regulated business is work nobody has been allowed to automate, because the tools on offer wanted the data sent somewhere else. Sandboxed models and a scoped deployment are how that changes.
Healthcare
HIPAA. Protected health information stays inside your environment, and an agent only ever touches the minimum record it needs.
Financial Services
SEC, FINRA, and GLBA. Supervision, retention, and a reviewable record of every action an agent took.
Payments & Retail
PCI DSS. Cardholder data is kept out of an agent’s reach by design rather than by policy.
Contract & Policy
SOC 2 programs, client contracts, and your own internal rules, which are often stricter than the regulator.
We build to the standard you are held to. We do not sell you a certification, and any vendor who offers you one for an AI deployment is selling you a logo. Bring your compliance team to the first call rather than the last one.
Our team does compliance implementation and cybersecurity and data protection as service lines of their own, so the people scoping your deployment are the people who do that for a living rather than a salesperson reading a checklist.
The Platform Underneath
We wrote the software the agents run on.
Which is the part most of this industry cannot say. When something should work differently for your business, we change the platform rather than filing a feature request with a vendor.
Wondering how an agent is actually engineered? That is the AI Agents service line, inside our AI and software practice. This page is the offer; that one is the build.
Common Questions
The questions owners actually ask.
Is this replacing our employees, or helping them?+
What kind of work can an agent actually do?+
Does it have to run in the cloud?+
We are in a regulated industry. Is that a problem?+
How many agents can we have?+
What happens when an agent gets something wrong?+
Do we need a technical team to run this?+
Where do you work?+
Let’s Talk
Name the job nobody wants to do.
Book a call with a senior member of the team. Bring the process that is eating the most time, and we will tell you honestly whether an agent is the right answer for it.