Axis is moving beyond collecting robot data. the new partnership with 𝐅𝐞𝐚𝐠𝐢𝐧𝐞𝐑𝐨𝐛𝐨𝐭𝐢𝐜𝐬 shows what that data infrastructure can look like when it meets real robotics hardware. Feagine is building soft embodied intelligence, including flexible robotic arms and its Fi0 cross-embodiment foundation model. through @Axisrobotics Suite, Axis will provide customized simulation tasks and trajectory data designed around the fine manipulation needs of Feagine’s robots. Both are working toward simulation data So the workflow becomes: 𝐬𝐢𝐦𝐮𝐥𝐚𝐭𝐢𝐨𝐧 → 𝐭𝐚𝐬𝐤 𝐠𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐨𝐧 → 𝐭𝐫𝐚𝐣𝐞𝐜𝐭𝐨𝐫𝐲 𝐝𝐚𝐭𝐚 → 𝐦𝐨𝐝𝐞𝐥 𝐭𝐫𝐚𝐢𝐧𝐢𝐧𝐠 If that loop keeps compounding, every new robot doesn’t have to start from zero. the experience generated for one type of robotic embodiment can help improve intelligence across others. that’s a pretty important direction for Physical AI. building more robots shouldn’t mean starting from zero every time, the data should compound we might start seeing the real agentic adoptions from here