Inner Sky Labs launches physical AI models beyond Miko children's robots
The AMW Read
The platform adds a supplier to the embodied AI player map, but repeats the previously covered launch and lacks independent evidence of reliable deployment across hardware.
Inner Sky Labs launches physical AI models beyond Miko children's robots
India's Inner Sky Labs announced a physical AI foundation-model platform on October 8, extending beyond its Miko children's companion robots. According to Inc42, the company is nearing a 3 billion Indian rupee (~$30.9 million) funding round involving YourNest Venture Capital, Keshav R. Murugesh and undisclosed global investors. If completed, the round would bring cumulative funding to approximately $100 million. Planned uses include real-world data collection, compute infrastructure and model training.
The strategic shift is from selling a specialized robot to supplying intelligence across robot manufacturers. The platform combines Drishti for vision, Shruti for audio and Sparsh for touch with Kriya, Prana and Karma for motion planning and action-outcome prediction. A separate Kavach safety layer checks actions against preset rules before execution. Inner Sky Labs says the models are developed in-house and designed for multiple hardware types, with cloud API, on-premises and device-side deployment options. This positions the company in the emerging horizontal layer for embodied AI, where the commercial question is whether capabilities developed around one product can transfer reliably to other machines and tasks.
For builders and investors, external deployment evidence is the concrete diligence priority. Children's conversational robots and industrial arms have different precision, control and safety requirements; Miko experience alone does not establish industrial readiness. The reported capabilities and more than 20 safety safeguards remain company disclosures, without detailed independent benchmarks. Buyers should seek measured performance on their own hardware and workflows, while investors should distinguish the pending financing from a closed round and verify external customer adoption and pricing, which remain insufficiently disclosed.
