Join us
How do we make AI maximally useful inside complex companies?
We’re obsessed with this question, and Ortelian exists to answer it.
Most of what AI needs to know was never written down.
Inside a company, the information you need is spread across systems, documents and people’s heads. Processes have exceptions, and decisions depend on things nobody thought to write down. Before AI can do useful work, someone has to get to grips with all of that.
What does an agent need to understand before it can act? Which decisions can it make? How do we know it’s doing a good job? And how much of the process should change once AI can do part of it?
We build the software for this and work inside companies to put it to use. What we learn in each deployment lets agents take on more of the work in the next.
Ownership matters more than credentials.
You’ll work directly with customers, often on site, and own a problem from the first audit until the solution is in daily use. We care more about what you’ve built and how fast you learn than about a degree or a job title. The work is hard, and we want people who enjoy that.
We plan to give early team members equity and a say in how the company is built.
The roles we’re building the team around.
We’re always interested in meeting people for these roles.
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Software Engineer, AI
Build the agents, their connections to company systems and the platform we use to run and improve them.
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Forward Deployed Engineer
Understand the customer’s processes, configure agents and connect their systems using our platform and AI tools. Own the deployment through testing, training and daily use.
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Product Designer
Figure out how people should work with agents: what they need to see, what they should control and how to make sense of the results.
If you want to work on this question, say hello.
Send Laurens a few lines about yourself and something you’ve built or figured out. We’d like to hear why this interests you.