Safety is what unlocks AI, not what limits it.
We build the governance layer that lets a business hand real work to AI agents and actually sleep at night. That is the whole company, and it is a bigger job than it sounds.
Our vision
We envision a world where safety is what unlocks AI’s potential, not what limits it. Where any company can give AI real work and trust it completely, without needing a team of engineers to manage it. The more secure AI becomes, the more it can do for the people who use it.
Our mission
We believe humanity should be empowered by AI. Omnafy governs what AI agents can access and do, cutting down on security leaks and giving businesses the confidence to hand AI real responsibility, real access, and real work. Governance is where we start. Empowerment is where it leads.
Why we started
Models crossed the threshold for real, multi-step office work, and the Model Context Protocol standardized how they call tools. What never arrived alongside them was the layer every business actually needs before it can say yes: identity, permissions, approvals, audit, and cost control.
So companies got stuck in the middle. On one side, chat pilots that impress in a demo and do no real work. On the other, automation nobody will trust near a production system. We kept meeting teams who had already built the clever part and were blocked on the boring part, which turns out to be the hard part.
We decided to build that boring part properly, as a product rather than a one-off integration, so that every company after us gets to skip the eighteen months we would otherwise all spend rediscovering it.
Forged in healthcare
Omnafy grew out of J&M Rapid Application Development’s years of building healthcare operations software. Our first agent workforce runs patient intake for a home health care provider, reading referrals, assembling charts, and checking eligibility. Every action touches PHI, and every mistake matters to somebody.
That is an unforgiving place to learn this craft, and we are glad we learned it there. You cannot ship an agent that usually gets it right when the output lands in a patient record. The constraint produced the architecture we now bring to every engagement: HIPAA-first, execution inside your own cloud, and clinical judgment permanently reserved for the licensed humans who are accountable for it.
If the governance holds up under PHI, it holds up for your industry too.
How we work
We are engineers, and we work the way we would want a vendor to work with us.
We sit with your team
- Every engagement starts by shadowing the people doing the work today
- The tool catalog, risk tiers, and approval policy get agreed together
- Your team reviews and approves what the agents are allowed to do
We leave you something you own
- The catalog specification is yours, not a dependency on us
- Execution runs in your cloud, on your terms
- Documentation for every operation we wrap
We say what we don't know
- Autonomy expands only where measured accuracy earns it
- If a workflow is not worth automating yet, we will tell you
- Judgment calls stay with the people qualified to make them
Come build this with us.
The discipline we work in barely exists yet. Running fleets of accountable AI agents against real business systems is not a solved problem, and we would rather be honest about that than pretend otherwise. It is also the most interesting problem we have worked on.
If you are a customer, we would like to hear what you are trying to automate. If you want to work on this, we would like to hear from you too. Either way, a real person reads the inbox.