Scenix's platform is model-agnostic and embodiment-agnostic — it builds digital environments where any robot can learn and be evaluated, not the robots themselves.
Yunzhu Li clarifies that Scenix is not building robots or robot brains — it builds infrastructure (software and digital worlds) for training and evaluating robots. The platform works with any robot embodiment and any model, allowing customers to place their own robot brains into the generated environments. ✦ AI generated
Yunzhu Li · a16z Podcast · 2026-07-28 · original ↗
starts at this moment · 27:19
“When people hear you're going into robotics, what they're going to envision is you're pulling out a 3D printer and you're going to be making hardware and then you're going to be programming the brain of a robot and sticking it in the robot and then you've got a robot. And I don't think that's what you guys are talking about here.”
What we have been building you can imagine is infrastructure with the software around this infrastructure for people to build worlds such that robots can learn and evaluate, and this infrastructure is naturally model agnostic and embodiment agnostic. For our customers right now they have all different kinds of robots — some are using a single robot arm, some are using a bi-manual, some are using a fixed arm, some are using mobile manipulators, some using grippers. Our platform is naturally embodiment agnostic. We can very easily integrate different kinds of robotic embodiments, put them into the worlds we generated, and be able to give those individual robots capabilities of doing the right tasks at the right levels of reliability and efficiency in the real environments. We are also model agnostic — we can use the data generated by our worlds to train different models either from scratch or doing post-training of existing foundation models like vision language action models or world action models. To us it doesn't matter, we just want to make sure we have the infrastructure and the worlds such that the robot can work reliably in the real environment.
verbatim transcript · starts at 27:19
27:19a 3D printer and you're going to be making hardware and then you're going to be programming the brain of a robot and sticking it in the robot and then you've got a robot. And I don't think that's what you guys are talking about here. So maybe talk about what you know where this fits in the life cycle of creating a robot and like where you will end and
27:39where the rest of the ecosystem will will begin. So what we have been building you can imagine is a infrastructure like with the softwares around this infrastructures for people to for them build words such that robot can learn and evaluate and this infrastructures is naturally model agnostic and embodiment agnostic. So I just want to be very clear just because this is actually a very subtle for you
28:04it's obvious but it's a very subtle point which is um from what you said that's not building a robot it's building an environment which another company can place their robot brain >> exactly >> to navigate and to learn. >> Yeah. So for our customers right now they have all different kind of robots. Some are using for them single robot arm some are using bio some are using a
28:26fixed arm. Some are using like a mobile manipulators. Some using grippers, some are using some more elaborate versions of the end factors. So our platform right now is just naturally embodiment agnostic. We can very easily integrate different kind of robotic embodiment be able to put them into the works we generated with digitalized such as we will be able to give those individual robots capabilities of doing the right
28:48tasks and at the right levels of reliability and efficiency in the real environments. >> Yeah. >> And we are also for example model agnostic. So we can just using the data generated by our words to train different models either from scratch or doing post training of existing foundation models like vision language action models or word action models. So to us it doesn't matter we just want to
29:11making sure we have the infrastructure we have all the words such as the robot can work reliably in the real environment. you know, you you you have uh told me um that you think uh a lot of the predictions around humanoids were a little bit aggressive and we're likely to see more constrained rollouts like warehouses or whatever. Can you talk a little bit about that and like how that
29:31impacts what you're going to be tackling here at uh the like world labs? >> So that's a very good question. So if you look at for example all the uh progressions of robotic applications in the real environments it has always followed the trend from going from fully structured environments into semiructured environments and then into unstructured environments. >> For fully structured environments what do we mean that you have knowledge and