janyl

A line drawing of a small office. In front, a man sits at his desk typing on a laptop; beside it stands a small upright screen showing two chat bubbles, his agent. Thin curved lines run from that screen to the four empty desks around him. Drawn in a uniform stroke with no fill and no shading.

Our method

We sell AI agents, but we don’t think of ourselves as a tech company. The value of our company lies in our method. It’s no secret what it is, but to do it well, you have to do it over and over. That’s what someone is buying when they build an agent with janyl.

The method starts with an audit, the first part of which is free and accessible from this site. We learn some basic things about your business to determine if and how we can help. Not every business will get value from an agent, and we’ll let you know if we think this is the case. As the audit moves on, we make a plan with your team about when to deploy your agent, for whom, and for what business domains.

The hallmark of a janyl deployment is that it starts with a single person on a single business problem. If an agent cannot provide value to an individual, it will never provide value to a team.

A janyl deployment grows organically. As the single person reaches for more colleagues or more tasks, janyl’s agent moves naturally into these domains and towards these people, coding only what it needs as it learns. This part of the process is supervised by a Forward Deployment Engineer, who makes sure that the agent is rewarded for positive interactions and outcomes, that it never cuts corners in terms of security, and that the foundational code it writes for itself is solid.

Over time, agents need to adapt to new systems, new employees, new models, new business objectives, and bugs in its own harness. Many of these happen automatically as part of the agent’s internal maintenance cycle. But it will, from time to time, need expert help and advice, particularly around questions of model choice and newly disclosed security vulnerabilities. janyl is there for that as well.

If you’ve worked in a larger organization, this process may sound radically compressed compared to other AI deployments. It is. But don’t confuse speed for a lack of quality. Our philosophy is that starting small with an agent that grows into its role is not only cheaper and faster, it is also the path to having the most customized and most autonomous agent possible.