Answer extracted from the Digital Construction Podcast podcast — listen to the full episode below.
What business model decision proved most effective for a platform targeting large construction enterprises?
The switch from token-based subscriptions to scan capacity pricing eliminated customer friction and unlocked sustainable growth. Customers feared tokens represented actual company spending, throttling adoption; moving to transparent capacity tiers—starting at 2,000 or 5,000 scans—made scaling intuitive and upselling effortless. This model remains the revenue engine today.
Why tokens backfired, and how capacity became the solution
Token-based pricing, borrowed from Autodesk's playbook, seemed logical on paper—customers purchase a pool of tokens and consume them as they work. But psychology intervened: users felt they were burning through real company dollars with every token, creating decision paralysis. They'd hesitate before running operations, afraid to trigger overspend, which strangled platform adoption just when momentum mattered most.
Cintoo's pivot reframed the entire transaction. Instead of abstract tokens, pricing became tied to a concrete, visual metric: the number of 3D scans a customer uploads to the platform. As Dominique Pouliquen explains in the episode, this transparency aligned customer perception with actual usage, removing the psychological barrier.
Subscription tiers built for easy growth
The new model operates on simple, scalable tiers. A customer might start with a subscription for 2,000 scans—a modest foothold that feels low-risk and achievable for a small project. As their team grows or their projects expand, they upgrade to 5,000 scans, then beyond, without friction or renegotiation. Each upgrade is a natural progression, not a complex commercial decision.
This structure eliminated a critical friction point: customers no longer feared running out of their allocation mid-project or felt they were wasting sunk costs. Instead, they could scale spend in lockstep with actual business growth, making the upsell feel inevitable rather than aggressive. The platform now has over 110,000 active users—a scale that owes much to this friction-free growth machine.
The beauty of the scan capacity model, as detailed in this podcast episode, is that it ties revenue directly to customer value. More scans mean richer 3D data on the platform, which means higher engagement and deeper integration into the customer's workflow—a virtuous cycle that sustains both adoption and retention.
"Everything takes longer than expected, and usually it's three times longer than what you think."
Dominique Pouliquen — Co-founder and CEO of Cintoo. Pouliquen joined Autodesk through the acquisition of RealViz, his first company, where he worked on photogrammetry technology. At Autodesk, he co-led the ReCap team in San Francisco, managing massive point cloud data and democratizing access across Revit, AutoCAD, and C3D. He later founded Cintoo with PhDs from another French laboratory who had developed breakthrough compression technology to stream high-resolution 3D meshes in web browsers.
If you want to hear more about the technical architecture that makes streaming these high-resolution 3D meshes possible—or the journey that led Pouliquen to leave Autodesk—the full episode dives deep into the compression innovation and early competitive challenges.
Key takeaways
- Token-based pricing created psychological friction—customers believed tokens represented real company cash, making them hesitant to adopt the platform.
- Switching to scan capacity subscriptions aligned pricing with actual usage, removing the fear of overspend and unlocking adoption.
- Simple tier progression (2,000 → 5,000 → higher scans) created a natural upselling path without commercial friction.
- The capacity model remains the primary revenue driver today, powering subscriptions and upselling across 110,000+ active users.
See also
Why did the founder leave a senior role at Autodesk to start a new company?
While leading ReCap at Autodesk, Pouliquen identified a major headache: the workflow was very desktop-centric and there was no easy way to upload, share, and collaborate on point cloud data across teams and the cloud.
What is the core principle behind compressing massive point cloud data into formats suitable for cloud sharing?
The technology converts huge point clouds into 3D meshes or 3D surfaces, which solves the problem that point clouds are like 3D dots in space where you see through them. 3D meshes represent continuous surfaces, making the data far more interpretable and compressible by up to 20 times.
What advice does Devon Middleditch give to early-career technical professionals aspiring to leadership?
If you are a technical person, it is easy to drift back to your safe space. Devon suggests taking professional development modules on understanding self and developing emotional intelligence as core skills for stepping into leadership roles.