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I'm currently building a product feedback intelligence platform where you can store all your customers and the related feedback they have provided. One specific feature I want to highlight is Ask AI.
It is a button that you can activate with a few clicks for any dynamic block that lists multiple records. Once enabled, it can answer questions based on the records being displayed.
Within the settings, you can define the welcome message, the specific instructions, and the personality of the assistant. It is a very flexible way to interact with your data.
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Note from Softr: If you want to jumpstart your build, you can use the AI co-builder to generate a complete CRM or feedback system with your database schema and blocks already configured.
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For suggested prompts, Softr will automatically suggest the most relevant options based on the available data. You can also customize the design settings to fit your app's look and feel.
In the live app, I can open the feedback list and activate Ask AI. It is great to see these suggested prompts, and you can give one a try immediately.
From there, you can ask follow-up questions and deep dive into your data. This functionality can save you hours of work by providing instant insights.
While this is a specific use case for product feedback intelligence, you can apply this to your own industry and use cases. It allows you to activate AI on top of your data in a very secure way.
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Note from Softr: For teams looking to manage high volumes of data, using Softr Databases ensures your feedback and customer records are managed natively with maximum performance and security.
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I have also activated this in another part of the app. If I open a specific customer record, I can see all the feedback filtered for that individual customer.
I can then use Ask AI to ask questions specifically related to that customer's feedback. This provides a highly contextual AI layer for the user.
Look back at your existing Softr apps to see where it makes sense to activate this feature. Adding this AI layer for the end user is incredibly easy to implement.
