Imagine buying a €1 donut for your team, only to realise that the manual administrative work of processing the receipt bumped the true cost up to €5. It is exactly this kind of everyday friction that frustrates founders, business owners, and employees alike. But for the minds behind FabricAI, Juhani Tolvanen, Jarkko Tolvanen, and Tuukka Seeslahti, this €5 donut wasn't just an annoyance; it was the spark that ignited a €3.2 million AI revolution.

In the rush to capitalise on the current tech boom, many companies fall for the AI hype, building tools that look great on paper but fail to change how work actually gets done. They slap an "AI badge" on their product and expect users to pay a premium. For FabricAI, however, the goal wasn't just to build a flashy AI assistant; it was to completely eliminate manual invoice processing by providing a complete, end-to-end capability. By shifting their pricing model from traditional SaaS subscriptions to an outcome-based "Neverlook" automation model, FabricAI is proving that customers don't want to buy AI; they want to buy results.

How a €5 donut sparked a €3.2 million AI business

Just like many great startup stories, FabricAI was born out of a desire to solve real-world inefficiencies. Before founding the company in 2018, the founders ran a small consultancy, which is where they encountered the infamous €5 donut. As young, tech-savvy entrepreneurs, they noticed a glaring operational bottleneck: up to 50% of an accountant’s time was tied up in reviewing, sorting, and approving purchase invoices.

"We were always thinking this cannot be true, that humans are doing this repetitive, boring manual work," recalls Head of AI Juhani Tolvanen. "There has to be a better way."

The solution was an AI-native product built from the ground up to replace human manual workflows rather than simply accelerate them. Supported by the financial backing and corporate ecosystem of the Visma Group, this autonomous approach is already transforming enterprise finance. In Norway, for example, FabricAI’s engine helped the Visma company Tripletex boost its revenue by 46 million Norwegian crowns last year alone. Today, the system handles over 1.5 million purchase invoices across 200 plus accounting firms and 65,000 end customer companies.

The math behind the model: Finding the right pricing alignment

While building an autonomous product is one challenge, monetising an AI-native business requires a fundamental shift in business logic. Traditional business software relies on seat licenses, charging companies based on the number of users. But for an AI-native company, this model creates a conflicting incentive: if the AI is highly efficient and eliminates the task entirely, the customer needs fewer users logging in, meaning the software company makes less money for delivering a superior product.

To crack the monetisation code, FabricAI aligned its revenue directly with transaction-level customer outcomes. They analysed the exact unit economics of manual invoice processing, which costs a business roughly €1.50 in time and labour per invoice. By contrast, FabricAI's autonomous system processes that same invoice for under 40 cents.

By charging based on the successfully completed, autonomous outcome rather than user access, FabricAI creates a clear financial return. The business saves approximately 90 cents per invoice, and they only pay when the technology successfully executes the work. For tech leaders, the takeaway is clear: monetisation succeeds when your revenue model is anchored directly to the economic value you create.

Scaling past the hype: Why customer trust is the ultimate metric

Transitioning a business to autonomous operations requires overcoming a massive trust barrier. In the early market, tech enthusiasts are happy to experiment with new algorithms. But to scale an AI-native product to mainstream business buyers, the technology itself must become a quiet, predictable utility.

"Each of these traditional pricing models that we implemented failed someone," Jarkko Tolvanen, Commercial Director, reflects. The breakthrough came when they realised that mainstream buyers view AI novelty with uncertainty; they want proven benefits, not complex technical jargon.

"When we move from early market to mainstream market, we need to hide the AI," points out Tuukka Seeslahti, Product Director of FabricAI. Mainstream users view AI as uncertain; they just want proven benefits. "The more AI you have, the less they are willing to pay for it because it's uncertain. They need to buy the proof."

Because outcome-based pricing means FabricAI only generates revenue when the customer's automation succeeds, their onboarding process functions like an operational performance guarantee. The company commits to a structural milestone with new clients, promising that they will reach a 30% "Neverlook" automation rate within just three months of integration.

If companies expect AI adoption to just happen automatically, they are making a critical mistake. Because of this, FabricAI's Customer Success team has become the real MVPs of the operation. These specialists work directly with accountants, listening to their worries about AI taking their jobs, helping them fix broken internal processes, and guiding them through the transition from active human oversight to autonomous delegation.

"Our job begins here when we get the signature," Jarkko Tolvanen emphasises.

The future of business software: Chasing the 95% Neverlook dream

For founders and entrepreneurs looking to scale AI, the lesson is clear: stop selling AI badges and start owning the end result. By deeply understanding the customer's friction points and anchoring their revenue to tangible client success, FabricAI has cracked the monetisation code.

Currently, FabricAI’s autonomous engine processes 50% of all of its clients' invoices completely never seen by a human. Backed by the operational scale of Visma, their roadmap is clear: to push that Neverlook autonomous rate to 95% by 2030.