5%
of the enterprise generative AI pilots MIT studied produced a measurable change in revenue or cost. The other 95 per cent did not.
Source: MIT NANDA and MIT Media Lab, The GenAI Divide: State of AI in Business 2025.
Operance AI
We are an AI consultancy and venture studio for leadership teams, and we turn AI spending into results that show in your figures. We find where AI pays, put it to work in the systems your people already use and keep improving it, so the advantage grows and stays yours.
Your board is asking what AI has delivered.
The licences are paid, a pilot or two is running, and people like the tools. Yet when the quarter closes, nobody can point to the figure that moved.
About 5 per cent of the pilots MIT studied did produce measurable value, and the companies behind them have an answer when the board asks. Getting your company into that group is our job.
We start every engagement with one named figure, one owner and a way to measure it from day one.
Two published figures
40%+
of agentic AI projects, where AI carries out tasks on its own, will be cancelled by the end of 2027, Gartner expects, because of escalating costs, unclear business value or inadequate risk controls.
Your competitors can buy the same AI tomorrow.
Every company can buy the leading AI models at the same price, on the same day, and used as they come they give much the same answers.
Your own track record is harder to copy: which quotes won, which customers stayed, the exceptions your best people handle, and what happened after each decision.
Setting AI up to learn from that record, inside your business, is the work we do with you. What it learns stays yours when a better model arrives.
MIT's researchers found that most generative AI systems “do not retain feedback, adapt to context, or improve over time.”
One cycle, repeated until the numbers move.
Before AI takes on any work, we agree with you which figure should move and how it will be measured. Then AI does its part, we measure what changed, and each cycle starts from what the last one taught. We call it the loop.
- Intent: We agree which figure should move.
- Execute: AI does its part of the work.
- Measure: We measure what changed.
- Learn: The next cycle starts from what this one taught.
And round again What we learn sets the next intent, so the four steps close into one ring, the loop.
AI pays when people, processes and platforms move together.
The AI Transformation Triangle is our own framework. Many organisations are strong on one side and thin on the other two, with good tools that few people use, or keen teams with no process to put the tools in.
Results come when the three work together, so the work gets done a better way, new tools reach the people they were meant for, and your systems carry the work from start to finish. Together these form your operating model, and that is what we redesign with you.
Hover over or tap a side or a layer of the triangle to see what it covers.
- People
- Everything that decides whether AI gets used.
- Processes
- Everything that decides whether AI delivers value.
- Platforms
- Everything that decides whether AI scales.
- Operating layer people × processes
- How the work gets done once AI is part of it.
- Adoption layer people × platforms
- Whether new tools reach the people they were meant for.
- Orchestration layer processes × platforms
- Whether your systems carry the work end to end, without a person stitching them together.
People
Everything that decides whether AI gets used.
Processes
Everything that decides whether AI delivers value.
Platforms
Everything that decides whether AI scales.
Plan it, put it to work, keep improving it.
Any of the three is a place to begin. The strategy tells you which work is worth paying for before you spend more.
Transformation
We redesign how your organisation works with AI.
We set the strategy with your leadership team, choose the decisions where AI moves your figures most, and redesign how that work is done.
What you get
A strategy you can act on, tied to the figure it is meant to move.
Implementation
We put AI to work in your business.
We bring AI into the systems your people already use, with the data and ways of working that make it part of the daily routine.
What you get
AI doing real work in your business, and everything we set up is yours from day one, in writing.
Optimisation
We close the learning loop, so every run improves on the last.
We measure what changed and feed each result back in. Every lost quote is recorded with its reason, so the next cycle can learn from it.
What you get
An advantage that grows with every cycle and is hard for a competitor to copy.
Our services, and what each one is for.
Each engagement uses a different mix, chosen for the problem at hand. You pay for what your problem needs and nothing more.
Strategy
Which decisions are worth improving with AI, what moving each one is worth, and what it would take. Done before any money goes into systems.
A clear go or no-go on each opportunity, with figures your finance team can check.
Education
Managers learn to read what the AI tells them, and the people whose work changes are brought along from the start, so the new way of working lasts.
Teams that understand what changed and use it in their daily work.
Data management
Where your figures live, how they are kept accurate, and a starting measurement taken before anything changes.
One set of figures everyone trusts, so meetings move on from whose number is right to what to do next.
Models
For when an off-the-shelf model is not enough. We train one on your own material, to sort your documents, read your images or do one task better than a general model.
A model trained on your material, with its accuracy tested and on record.
Generative AI
Drafting, summarising and answering questions from your own documents and data, with every answer traceable to its source.
Answers people can check before they act, and regular tests that show how often they are right.
AI agents
AI that carries out a routine task on its own. Each agent has one named job, written limits on what it may decide, and a person who handles the exceptions.
Routine work done without someone driving it, and every action logged, so an audit is a quick search.
Applications
The screen your people open every day, designed around their working day so it is still in use on a busy Tuesday afternoon.
A tool people choose to use, owned by your organisation.
Integrations
AI connected to the tools your people already have open: your ERP, your CRM, your warehouse system.
Nothing new to log in to, so nothing gets skipped.
Monitoring
Every change is tested before your people see it and watched once it is live, so a drop in quality shows in your own reports.
Each improvement arrives with its before and after figures on record.
Responsible AI
What the AI may decide on its own, what goes to a person, and how you would show both to a regulator. European rules, the EU AI Act, are coming into force in stages, and designing for them now costs less than adding them later.
A written record of what it decides alone, where a person signs off and how it was tested, ready before anyone asks.
Security
AI that acts on its own can be tricked or misused. We test it the way an attacker would, from hidden instructions to data leaving by the wrong route, and close the gaps we find.
Every test on record, and the gaps we found closed before launch.
Managed AI
Once it is live, we keep it running: questions answered, models replaced when a supplier retires one, quality watched and costs explained.
When a supplier retires a model, the switch is already planned. You choose in writing whether we run it or your team does.
Operance AI Studio is where we build.
Operance AI Studio is our venture studio, where we build AI products, tools and workflows. We work hands-on with the tools below, so we can tell you which fit your business, which to skip and what each costs to run. You stay free of any one vendor.
- Anthropic
- OpenAI
- Mistral
- Gemini
- Llama
- Hugging Face
- Ollama
- NVIDIA
- Perplexity
- GitHub
- Composio
- Kling AI
- OpenRouter
- DeepSeek
- Qwen
- Kimi
- GLM
- Google Cloud
- Snowflake
- Databricks
- Stripe
- Zapier
- Make
- n8n
- Lindy
- ElevenLabs
- HeyGen
- Midjourney
- Runway
- Higgsfield
- fal
- Apify
- Supabase
- PostgreSQL
- DuckDB
- Spark
- Airflow
- Python
- PyTorch
- LangChain
- Hermes
- OpenClaw
- FastAPI
- Redis
- Kubernetes
- Docker
- Terraform
The people who set your strategy stay to make it work.
Operance AI is an AI consultancy and venture studio with offices in Den Bosch, the Netherlands, and Melbourne, Australia. The team that sets your strategy also puts it to work and stays with it, so accountability never changes hands. Between the two offices we cover European and Australian working hours.
Where we work fromLocal time now
- Den BoschThe Netherlands
- MelbourneAustralia
Peter Sprenger
Arno de Kloet
Jonathan Vandionant
Sion de Jong
Wesley Romeijnders
The questions that come up first.
Answered here, so you can forward this page to whoever else has to sign.
Our data is a mess. Is it too early?
Sometimes, and we will say so. If the data already exists as a by-product of daily work, untidy is workable. If someone would have to be hired to produce it, that becomes the first piece of work.
Do we need AI experts of our own?
No. We bring the AI expertise and work alongside your IT team where you have one. From you we need a leader who owns the result, and time with the people who do the work today.
What does it cost?
The first piece of work has a fixed price for a fixed scope, quoted once we know which decision you want examined. It is the smallest commitment we offer. Every later phase is priced on its own in the proposal, next to the figure it is meant to move, so you can decide on the numbers.
How long before the results show?
If the figure is already being measured, you can track movement against it from the day AI goes live in your business. If not, measuring it is the first step. Either way, your proposal states when the first measurement is taken, so before you sign you know when you will see whether it moved.
Who owns the work and the data?
You do, from day one, in the contract. That covers your data, what we set up for you, its settings, the material any model is trained on and the documentation. Where each part runs is agreed in the contract. When a better AI model arrives, what the system has learned about your business stays with you.
The conversation.We listen first to how you work and where you want to grow, then show you where AI would make the biggest difference to your results.
The plan.A written proposal covering what we will do, what it will deliver, what it costs and how the result will be measured. Everything we set up is yours. If you want us to keep it running and improving after launch, the proposal prices that too.
Tell us a little about your business and what you want to improve. A consultant will reply within two working days to arrange a conversation.