Deploying AI inside
complex companies.
Our engineers work inside your company, find where the work is held up and put agents on it that run the process end to end. We stay to keep them running, so you get more done with the team you already have.
Agents
Build AI into the way the business runs.
Agents take on ongoing work on their own, within the goals and limits your team sets. They follow what is happening, investigate what matters and act on what they learn.
A chat assistant
- You notice a change or a question
- You ask and paste in the context
- It answers from what you gave it
- You act check, decide, follow up
An agent with a job
- It notices a change that matters to its job
- It gets context from the world model
- It decides what the change means for the work
- It acts or asks you first
Done by you Done by AI
World model for knowledge work
Agents guess when they don’t know the business.
A model that lacks the facts still gives an answer. In company work, the facts are spread across your systems, people’s heads and the world outside the company.
Ortelian joins them in a world model for knowledge work. Agents work from it instead of guessing, and every finding links back to its source.
01 · Software
The code holds everything the work needs.
That’s why AI took off in software first.
02 · Internal knowledge
A wiki holds what the company writes down.
That’s enough for questions about the company itself.
03 · Knowledge work
Your work also depends on the world outside.
Customers, competitors, regulations, people moving. We join it with what’s inside, in one model.
Inside the company The world around it
How we work
Audit. Redesign. Build. Deploy.
A chat assistant gives people access to AI, but the work runs the way it did before. People can’t fully describe their own work, so our forward-deployed engineers work on site, watch the work and find the constraint before we build.
- 01 Audit
We map your business processes, find the constraint and prioritise what to tackle first. The assessment reflects how the business actually runs, not how the process is written down.
InputsPrepareWork waitingConstraintDecisionActResultIllustration · a queue can reveal where the flow is constrained. - 02 Redesign
We redesign the process from first principles around what AI can now do. We remove unnecessary steps and define how agents, software and people work together, including what agents can decide, do or escalate.
- 03 Build
We build the agents and workflows on Ortelian’s platform and connect them to your systems. Evaluations based on real examples check whether the work meets the standards agreed with your team.
- 04 Deploy
We put the system into daily use. Your team works with agents through Slack and email, without having to become AI experts. We stay to keep it running and use feedback and evaluations to improve the work.
The audit shows where the work is held up. For example:
- Go-to-market
Track companies and market changes, investigate emerging needs and decide where your team should focus.
- Finance
Watch customers, suppliers and regulation for changes that affect credit, cash or compliance, and prepare the response for your team to review.
- Operations
Follow supplier and logistics events through to the orders and people they affect, and take the next step within agreed limits.
Who you’ll work with
Laurens Nys, founder.
Laurens founded Ortelian. He builds the platform and works directly with customers, from the first audit through implementation and ongoing operation.
Your advantage
Your advantage is what your company learns.
Your competitors can use the same AI models. The advantage comes from what those models have to work with.
Every job adds to your world model: what your people know, what agents find and how decisions turned out. Each piece of work starts from more than the last, so a company that starts earlier has more to build on.
The model can be rented. The world it works in cannot.
How to start
Tell us where the work gets stuck.
You don’t need to know yet what AI should do. Finding that out is what the audit is for.
- 01 A call
We talk through the business and where the work waits, and decide together whether an audit is worth it.
- 02 A two-week audit
We spend time on site with your team, map the work, find the constraint and agree the first build and how we’ll measure it.
- 03 Two-week cycles
We build, test and deploy in the tools your team already uses until the job meets the standard, then stay to keep it running.
Questions
Frequently asked questions.
Where do you work?
We work with companies in Europe and the US. We travel to your offices and work on site with your team.
Who is Ortelian a good fit for?
Companies with complexity in their team, product, service or market, where the work depends on context that no single system holds. If a process is simple, an agent doesn’t need that context and you probably don’t need us. We work best with teams that want to become AI-native and are ready to move quickly, give feedback and put improvements into practice.
What does AI-native mean?
We use four questions. Does AI own actual work, rather than only answer questions? Do agents share a current picture of the business and the world around it? Has the work been redesigned around what AI can now do? Do agents improve from feedback and evaluations? A company that can answer yes to all four is AI-native.
Why do you work on site?
People can’t fully describe their own work, and written processes rarely show the workarounds, pressure and edge cases that shape it. You only see those by watching the work. As models improve, this matters more, because better AI changes the work faster.
What do we need before starting?
An internal owner, ideally a founder or someone on the leadership team, with the authority to make decisions and drive implementation. A team willing to test, give feedback and iterate with us.
How is Ortelian priced?
You pay for implementation and ongoing platform use. The audit is a fixed fee, credited against the first build if you go ahead. Each build is a fixed fee agreed at the end of the audit. The platform is a monthly fee sized to your usage, with unlimited users and no annual commitment.
How do we know the work is good enough?
Evaluations built into Ortelian test whether agents meet agreed standards on real examples of your work. We repeat them as the system changes and track quality, cost, completion time and human effort.
What can an agent do on its own?
We agree what agents can access, what they can do and which decisions need approval. Those limits are part of the deployment and are reviewed as the work changes.
What happens after launch?
We keep the system running and improve it as the business changes. We review failures, update the knowledge, instructions or workflows, and rerun evaluations to check that the changes improve the work. Over time the platform and your team take on more of the day-to-day changes, and our engineers spend their time finding the next constraint.