After more than a decade working inside the engine room of CPG analytics, Sous’ CEO and Co-founder Alice Mintz knew the industry was ripe for change. As a long-time consultant for Spins, she spent her career helping brands interpret syndicated data and turn it into strategy. But the work was slow, manual and often overwhelming – for both analysts and the brands relying on them.
That’s where the idea for Sous was born – a CPG-specialized AI analyst designed to remove friction, democratize insights and give every team member the ability to “chat with their data,” Mintz said.
Sous’ AI compiles syndicated point-of-sale and retail data to narrow down relevant metrics like velocity, distribution, promotional strategy, retailer nuances, innovation patterns, consumer sentiment and cultural context.
Sous enables CPG brands to ask questions directly into the platform, Mintz explained.
The system can run both standard and advanced analytics instantly. And it can perform the kind of work analysts normally spend hours or weeks producing.
For example, a velocity quintile analysis – something notoriously tedious – becomes trivial: “Sous, because it’s AI, can run it very quickly, and also look at it from different angles.”
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Beyond KPIs, Sous incorporates qualitative signals to contextualize market behavior. Mintz describes it as a holistic analytical engine.
“Sous is able to look across and leverage both qualitative and quantitative information,” which “is a critical differentiator to give you full context.”
At the core of the platform is what the team calls the knowledge graph.
“It’s all about relationships. How do these different pieces of information connect to each other” to tell a story, she said.
Identifying the gaps in CPG analytics
Despite the rise of automation and dashboards, Mintz saw a structural gap in the industry: Access to data wasn’t the problem – interpreting it was.
These traditional tools “will not speak to you” because “there is always the need for an analyst or someone who understands the industry very well to find an insight and recommend an action,” she explained.
And those analysts are hitting limits.
“With any analyst or basically a human, there are always bandwidth constraints. But we also have just a mental capacity element. You can’t look across everything,” Mintz emphasized.
Generic AI models, like ChatGPT and Claude, were fast and “great at foundational understanding” but limited in capturing the nuances of the food and beverage business, she said.
Ultimately, Sous aims to make data approachable.
“If you’re daunted by our tool, then we haven’t made progress from the old way of working, which is people being daunted by data. … we don’t need to be that way anymore.”
For Mintz, AI isn’t replacing analysts – it’s helping them. As she puts it, “It feels like a massive creative unlock.”
