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Smart home manufacturer SwitchBot is known for a variety of products, ranging from home curtains to smart locks and robot butlers. Its long list of products is controllable through the dedicated SwitchBot app, and that experience is getting a major upgrade now.
The app is picking up a fully functional LLM-based generative AI assistant, known as Kata AI. This assistant can answer and act on natural language queries about SwitchBot-branded smart home products, activate new devices, create new automations, or even troubleshoot issues, the company said in a press release.
As you would expect, Kata AI supports both voice and text-based inputs, enabling device owners to choose the best way to engage with the chatbot. The assistant will require users to be on version 9.29 of the SwitchBot app or newer, with a dedicated option appearing on the home screen for easy activation.
Kata AI will let you control multiple connected smart home devices with a single command and identify SwitchBot products for activation using just photos of the retail packaging. As you can see in the screen above, it looks like like Kata AI will arrive in beta, at least initially.
A quick glance at the Kata AI FAQs page reveals that the chatbot can only be accessed 100 times per day, though this could change in the future. It looks like the chatbot interface will display the number of requests left for the day, though the company hasn’t confirmed this. SwitchBot notes that Kata AI won’t automatically act on a command in instances when you have two devices with the same name. In such cases, the chatbot will seek the user’s confirmation before performing the action.
Meanwhile, troubleshooting problems with your smart home device should be simplified thanks to the upgraded experience, the company says. SwitchBot app users will have instant access to all the online documentation, including manuals, videos, and FAQs, directly via the Kata AI assistant.
While this is ostensibly a great feature addition meant to enhance the user experience, we’ll reserve judgment until we actually hear some feedback from users.
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