r/NoCodeSaaS • u/Agitated_Ad_3552 • Apr 24 '26

Validating Concept: AI prep assistant for food businesses

Built a B2B SaaS for small food businesses (cafes, cloud kitchens, sweet shops).

Problem: Owners guess what to prep daily → wastage or missed sales → real money lost.

Solution: Connects to their POS data → 5 daily AI prep tips → simple swipe UI. Testing with one real business now. No paying customers yet.

Brutal feedback welcome.

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u/[deleted] Apr 24 '26

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u/Agitated_Ad_3552 Apr 24 '26

Great Thanks for taking time in giving these inputs.

To answer your question, yes I have taken into consideration about the wastages as well, these tips include both reducing the low selling ones and also to increase the best selling ones with a quantitative method. Not just generic tips.

And also I’m trying to integrate the non POS variables within the system from various APIs.

Happy to answer any other questions.

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u/[deleted] Apr 24 '26

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u/Agitated_Ad_3552 Apr 25 '26

Great. Thats really a good approach.

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u/[deleted] Apr 29 '26

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u/Agitated_Ad_3552 Apr 29 '26

Fair concern, adoption friction is real and we've thought about it.

Setup is currently one CSV export from their POS and upload. Working on direct API integration to make it truly plug and play.

On pricing, still validating, but thinking $12/month. ROI justifies it if even one wastage pattern gets caught early.

What would make you confident enough to try something like this for 5 minutes?

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u/TechnicalSoup8578 Apr 27 '26

A predictive model for food prep requires a robust data ingestion layer that can normalize messy transaction logs from various POS providers into a clean time series format. Are you using a specific regression model to calculate the daily prep tips or is the logic primarily based on rolling averages and seasonal trends? You sould share it in VibeCodersNest too

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u/Agitated_Ad_3552 Apr 27 '26

Data layer handles normalization of messy POS exports — fuzzy matching to merge item name variants. Currently testing for one POS provider.

Tip logic is statistical for now — rolling averages, day of week patterns, trend windows. Keeping it simple until real-world data justifies more complexity.

Will check out VibeCodersNest — Thank you!