The only AI agent built for FMCG
Meet Radish. Built on 5 billion data points a month from 150,000 real households who are searching, cooking, planning and buying every single day. That's the Appetise dataset: real behaviour, at scale.
ChatGPT knows the internet. Copilot knows your Sharepoint. Radish isn't a generic AI tool - it knows FMCG. It's trained to work fluently with the data your team already lives in - scan, shopper, ex-factory, panel and U&A - so it understands your category, your customers and how the industry actually works. Then it layers in Appetise's first-party behavioural data: the full picture, from consideration to completed basket.
The work that keeps your team busy for weeks like category reviews, brand plans, innovation research, pricing and promotion analysis comes out as finished, retailer-ready output in a single session.
Most AI tools only know what you feed them. Radish combines billions of behavioural data points from ANZ shoppers with the scan, panel and ex-factory data your team already uses. One without the other is a half-picture. Together, it's the full story.
Every workflow and output is trained on how FMCG teams actually work. That's why Radish doesn't just answer questions - it builds category reviews, brand plans, JBP decks and promo analysis. This is why you wouldn't use ChatGPT or Copilot.
Radish does the work that eats your week and produces retailer-ready outputs. Your team stops being busy pulling data and starts driving strategy.
Every workflow and output is trained on how FMCG teams actually work. That's why Radish doesn't just answer questions - it builds category reviews, brand plans, JBP decks and promo analysis. This is why you wouldn't use ChatGPT or Copilot.
Tell Radish what you're working on, like a category review for Woolies, a brand plan for next year, a JBP prep, or a NPD opportunity. Upload your scan data, your last review, your brand strategy - or don't. Radish already has the Appetise dataset and the FMCG context to start immediately.
It pulls the data, connects it to real shopper behaviour, builds the narrative and structures the output. This is finished, retailer-ready work, such as slides, analysis, recommendations, built on your data and ours.
You spend your time sharpening the story and making the call, not pulling numbers or building decks. Every session builds on the last, so Radish gets sharper on your brand, your category and your retailers over time.
