Ortelian vs building in-house:
you own it either way.
With Ortelian, you do build in house. Your team builds on our platform, and you own the IP, the data and everything built on it. We don't share it with anyone. What you skip is building and maintaining the infrastructure underneath: the agent harness, the knowledge graph, the data pipelines, the evaluations and the monitoring. That is a product company's worth of work, and it is the company we are.
Ortelian is a knowledge graph plus inspectable data pipelines for your company's operations, deployed with our forward deployed team on site. It is a platform plus a team, not a consultancy. After implementation, your team runs it, including your own agents working with it headless, or we keep running it for you.
At a glance
The question is not who owns it. It is what your engineers build.
You own the result either way. The real choice is whether your engineers spend years building and maintaining the platform underneath, or build on one that already exists and put their time into the work that is unique to you. Ortelian starts with the work: an audit on site, then builds in two-week cycles. Access to the Ortelian platform is part of an engagement, and there is no self-serve product. If you are also weighing a company-wide assistant, see Ortelian vs Glean.
When to build in-house
When the platform itself is your product.
Build the whole stack yourself if an agent platform is what you sell, or if you are ready to fund a permanent team to build and maintain a harness, a knowledge graph, data pipelines, evaluations and monitoring. That work never finishes, because models, systems and the work itself keep changing.
If a process is simple and an agent needs little context, a small internal build may be all you need. Keeping your IP in house is not a reason to build the infrastructure yourself. With Ortelian you own it anyway.
When to choose Ortelian
When your edge lives in how your people work.
Core IP is where Ortelian fits best. The more your advantage lives in knowledge work, in how your people plan, check, decide and sell, the more it matters to capture that in a knowledge graph you own instead of in scattered prompts. Most of the effort goes into knowing how the work really runs, redesigning it with the people who do it and agreeing the standard on real examples. We work on site not because our product needs it, but because your company does. The steps are on how we work, and the full method is in our guide on how to deploy AI agents in an enterprise.
The platform is the part an in-house team would otherwise build first. Agents work from a world model for knowledge work: your systems of record joined with outside sources, organised by an ontology we define with you, with every fact keeping its source. Each agent gets only the tools its job needs, every action is recorded with the sources behind it, and evaluations keep running after launch. Workshops during the build prepare your team to own the work. After launch, they run it or we keep running it for you. Either way, we host and operate the platform. It is hosted in the EU, agents use models with zero data retention, and you own your data and world model and can export both. More on what an AI-native deployment partner does.
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
Can you combine them?
Yes. That is how it is meant to work.
Your engineers build on the platform instead of under it. They can keep building the AI in your product and build internal agents on the same knowledge graph, while the infrastructure is already there. Workshops during the build prepare your team to take on more of the work over time.
Because the platform can run headless, agents your team builds can work with the same world model through scoped tools, once that is set up as part of the engagement. Your own agents then start from the same picture of the business instead of rebuilding it. We agree in the audit which systems and sources each side uses.
Other comparisons: Ortelian vs Glean, Ortelian vs AI consultancies, Ortelian vs Microsoft Copilot, Ortelian vs ChatGPT Enterprise and Ortelian vs Sierra.
Questions
Questions buyers ask when comparing.
Do we still own the IP if we build on Ortelian?
Yes. You own your IP, your data, your knowledge graph and what your team builds on it. We don't share it with anyone. You can export your data and knowledge graph along with the full history of how your agents were set up.
Is it cheaper to build AI agents in-house?
It depends on the team you already have. An in-house build costs the people who build and maintain it, the models and infrastructure, and the time before the first agent does useful work. Ortelian comes as an engagement that starts with an audit. We agree the scope, support and commercial terms with you before work begins.
Can our team take over after launch?
Yes. Workshops during the build prepare your team to own the work. After launch, your team runs it or we keep running it for you. Either way, we host and operate the platform, and the evaluations keep running on the work in use. Over time your team takes on more of the day-to-day changes.
Can agents our engineers build use the Ortelian platform?
Yes, once it is set up for you as part of the engagement. The platform can run headless: your own agents and AI tools, such as Claude or ChatGPT, work with the world model through scoped tools, and each one only gets the access its job needs. There is no self-serve product.
Do we lose control or get locked in?
You own your data and world model and can export both, along with the full history of how your agents were set up. Ortelian works across AI models and tests them against your work, so the world model and working methods stay when models change. Each agent gets only the tools its job needs, and anything that leaves the company waits for a person’s approval.
When should we build it ourselves instead?
When an agent platform is the product you sell, when you want to fund a permanent team to build and maintain the infrastructure, or when a process is simple enough that an agent needs little context. Keeping IP in house is not a reason on its own, because with Ortelian you own it either way.
Let’s work out the fit.
Bring the work that matters most and what your team has already built. We'll show you what your team would build on the platform, and what you would no longer have to maintain.
