Business automation with bots
We write down how your company really does its work, then give every person a bot, with its own computer, that does the busywork. Each bot acts only for its person and asks before anything that matters. It all runs in your own cloud.
For companies of roughly 20 to 500 people.
The problem
Every company has someone who “just knows” how month-end close, the vendor portal, or the big customer’s quirks really work. When that person retires or leaves, the know-how leaves with them.
Where a process is written down at all, there are three versions and nobody follows the current one. Quality depends on who happens to do the work that day.
Ask where last quarter’s payroll actually went, job by job, and the honest answer is a months-long project or a consultant’s invoice.
AI alone doesn’t fix this. A bot that doesn’t know how your company does things will guess. The model isn’t what’s missing. What’s missing is that nobody wrote the job down.
How it works
Bots, also called AI agents, are only as good as what they know about your work. So we start there.
A bot interviews the person who knows the job and drafts a playbook: the goal, the steps, the tools, and examples of good and bad results. That person corrects it and signs off. A person can follow a playbook, and a bot can run one.
Each bot works for one person and runs playbooks on its own computer in the cloud, with its own browser, files, and apps. It uses the systems your people already use. Nobody has to learn new software.
The bot’s person approves anything that changes a record, sends a message outside the company, or spends money. The rest just gets done.
Leaders get one map of every workflow, step by step: who or what does each step, who reviews it, and what it costs in time and money. Ask “is anyone already working on this?” and get an answer in seconds, not after a meeting.
Update a goal or a playbook in one place, and every team and person below it sees the change. Once a job is written down, it stays written down. Know-how only goes up, and it stops walking out the door.
Built to be trusted
Companies are right to be careful about software that acts on its own. Every bot we build runs under the same four rules.
Each bot works for exactly one person and signs in as that person. It never holds more access than they do, and it is never a shared account that can reach everything.
Each bot’s computer is isolated from every other bot: its own files, browser, and schedule. Bots coordinate through messages, not a shared disk, so one bot going wrong doesn’t become everyone’s problem.
Everything runs in your own AWS account, or Azure if that is where you already are. Identity, keys, audit logs, data, and calls to AI models stay there. Nothing gets exported to a vendor’s platform to be automated.
Every bot action and every approval is recorded. The map of your work is built from what actually happened, not from what someone remembered for a slide.
Privacy isn’t something we bolt on after the bots are running. We decide it before the first one starts.
Getting started
You don’t need a company-wide program. The first engagement takes about six weeks and covers one department.
Week 1
We lay out the department: its goals, its teams and people, the work in flight, and what that work costs today.
Weeks 2 and 3
We write 5 to 10 playbooks for the jobs the department repeats most, each signed off by the person who does it.
Weeks 4 and 5
Bots run those playbooks on their own computers, with their people approving anything that matters.
Week 6
A before-and-after readout: what got faster, cheaper, or more consistent, and what didn’t.
If the numbers hold, the bots take on more. If they don’t, you found out cheaply.
Built on work we already run
For one customer, a bot reads documents that arrive in a different format every time and returns checked results. A person reviews each one before anything is saved. The real work was writing down what a correct result looks like and testing the bot against real examples. Once that was written down, the bot did the job the same way every time.
At Assurant, our founder built a case management system from scratch that became one of two business-critical systems at one of its most profitable companies. At Northstar Memorial Group, he built an inventory system with a map overlay that saved millions in implementation costs. Since 2014, RAZR Systems has built for enterprise, nonprofit, education, finance, real estate, and automotive customers. See our Work.
Custom software
The bots run on the same engineering we’ve done for twelve years. We still design and build custom web applications, mobile apps, and the platforms they sit on. We stay after launch with support, growth, and technical leadership alongside your team.
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Bots ask before anything that matters
Nothing leaves your account to get automated
A before-and-after readout every time
Tell us about one department and the work it repeats every week. We’ll tell you plainly whether bots can help, and where to start.
Tell us which department or job you have in mind. Reach out directly or schedule a call.