I first encountered Haply in 2020, when I was CTO at ForceN Robotics. I remember trying the first generation of what would become their now world-recognized Inverse3 device.

It was immediately addictive. Not in a gimmicky way — but in the way great tools are. Interacting with a 3D digital world felt intuitive, almost obvious.

Even then, the Haply Leadership team had a clear ambition: solve the bottleneck at the intersection of Physical AI and Spatial Computing. If you can compress the gap between human intuition and machine execution, you don’t get incremental gains — you get a step-function change in robotics productivity.

Six years later, one thing is still true: robots still struggle to manipulate objects. 

For humans, grasping, repositioning, adjusting force — these are reflexes. In robotics, this remains one of the core constraints in advancing the field. We’ve made great strides in using videos to learn human motion, capturing how people move and interact with the world. Yet even an average person can see that the motions of robots remain slow and awkward. Teaching robots intuitive control at scale is still unsolved.

Vision can tell a robot where things are, Haply tells a robot how they should feel and move. That’s the reflex layer that transforms manipulation from guesswork into skill. This will allow robots to move with precision and speed - two important aspects of productivity. 

Whoever defines this reflex layer will shape the trajectory of physical AI.

Haply has quietly become the leader in three critical areas:

• The standard interface for teaching robots new skills
• The “touch” validation layer for simulated worlds
• The most intuitive bridge between human intent and machine action

Among Tier 1 robotics customers, the consensus is consistent: Haply’s platform is best-in-class in both intuition and scalability.

But technology alone doesn’t build a category.

What has impressed me over the past five years is the team’s deliberate approach to building their platform. World-class robotics platforms require more than elegant hardware and clever software — they require deep customer empathy and the discipline to ship value inside complex systems.

The Haply team understood early that the goal wasn’t to build impressive demos. It was to change behaviour at scale.

There were moments when some skeptics (rightfully) questioned their decision to work across multiple applications instead of narrowing into one vertical. It looked harder. It was harder. But it was intentional.

They chose a platform-first strategy over a task-specific one.

That conviction is now paying off. Years of iteration across customers have resulted in something rare: the most intuitive control and learning layer for digital-physical systems.

The Inverse3x controllers and Miniverse only demonstrate the surface of their capability. Underneath, Haply is building something deeper — closing the loop between sensing, simulation, and real-world action.

In a world dominated by vision-based robotics, Haply is pushing the industry forward by standardizing manipulation not through prompts or Cartesian commands, but through human reflex.

That is why Two Small Fish is proud to back Haply alongside Sound Media Ventures, Amazon, Hanwha, Business Development Bank of Canada, and Hustle Fund.

We believe the reflex layer of robotics will define the next decade of physical AI — and Haply is building it.