Robots are maturing. AI models are advancing. Deployments are rarely scaling. Today, deploying a robot still means stitching together systems that were never designed to work together. For every robot. Every time. The industry needs a unified intelligence infrastructure that any robot, any model and any workflow can plug... into. We call this an intelligence grid. Infrastructure that makes intelligence composable, deployable, and continuously adapting. Every connected robot evolves as the platform advances. More on what we're building:show more

More on what we're building:

Deep dive:

I recommend changing the orientation of the wrist for the Flexiv Teleop setup, something like this is better: Avoids the singularity between J5 and J7, and gives more dof that's needed for wrist pitch and yaw.

This is a massive vision. In digital automation, we’ve seen how middleware like n8n or Zapier unlocked the industry by making APIs 'composable.' Doing that for hardware where the variables are physical and unpredictable is the final frontier. A unified grid that handles the 'translation' between models and actuators is exactly how we get robots out of labs and into the real world. Very curious to see the documentation on the 'continuous adapting' part!

Unified intelligence grid streamlines integration toil and unlock scalable robot deployments. I'd love to hear how you plan to scale this?

This is the core bottleneck right now. The technology exists, but integration is still too fragmented. Without a common layer, scaling deployments becomes slow and expensive. An “intelligence grid” approach could standardize how robots, models, and workflows connect, making deployments repeatable instead of one-off projects. #Robotics #AI

composable intelligence is the right frame.