I was checking what was happening with diet trends. Tastewise gave me a clear answer in two clicks. Much faster than anything else we use.
increase in sales conversions for teams using Tastewise sell-in narratives.
AI Palette helps teams generate and screen concepts faster. Tastewise helps teams understand which concepts are backed by real demand, and gives them the evidence needed to secure buy-in, support investment decisions, and move concepts toward launch with confidence.
Trusted by 80% of the world’s leading food & beverage brands · since 2018
Tastewise combines consumer panels, market trackers, and AI agents to help teams expand distribution, accelerate innovation, and drive demand. It helps innovation teams identify opportunities, validate concepts, understand demand drivers, and generate explainable evidence that supports gate reviews, leadership approval, retailer conversations, and commercialization decisions.
AI Palette is an AI-powered innovation platform built around trend discovery, concept generation, concept screening, and innovation acceleration. Its tools help teams identify emerging opportunities, generate concepts, evaluate ideas, and prioritize innovation pipelines more efficiently.
Concept generation and concept validation solve different parts of the innovation process. Here is how each one shows up across the workflows teams rely on.
| Business need |
Built for the investment question
Validate demand, build the case, decide what to back. |
Built for the pipeline question
Trend discovery, concept generation, screening, and prioritization. |
|---|---|---|
| Data sources | Consumer panels, home cooking panel, foodservice operators, retail and eRetail trackers, consumer surveys, and AI-powered analysis | Global trend, innovation, consumer preference, product launch, and competitive datasets |
| Data freshness | Live, continuously updated consumer and market signals | Continuously updated trend and innovation monitoring |
| Primary use case | Validating demand, identifying opportunities, building the business case behind concepts, and supporting commercialization decisions | Generating concepts, identifying trends, screening ideas, and accelerating innovation pipelines |
| Evidence and activation | Explainable, bespoke, and repeatable evidence designed for gate reviews, leadership alignment, retailer conversations, and activation | Trend discovery, concept generation, concept evaluation, and innovation workflow support |
| Execution assets | AI-generated concept briefs, evidence packs, growth stories, one-pagers, activation recommendations, and decision-ready outputs | Concept outputs, trend reports, innovation recommendations, and screening reports |
| Ideal user | Marketing, Insights, Innovation, Sales, and R&D teams responsible for validating concepts and securing approval | Innovation and R&D teams responsible for concept generation and pipeline development |
| AI capabilities | Food-trained AI agents that identify opportunities, validate concepts, generate narratives, and recommend next actions | AI-powered trend discovery, concept generation, concept ranking, and innovation support |
| Best suited for | Teams solving the investment question: should we move forward with this concept? | Teams solving the pipeline question: which concepts should we explore? |
Watch how innovation teams validate consumer demand and build the business case behind their strongest concepts.
Strong concepts need more than a high screening score to move forward. The challenge begins at the gate review, when teams need evidence behind a concept, not just a score, and that is a different job from concept generation.
Move past a concept score to evidence that the opportunity is worth funding.
Confirm consumers want it and understand why interest is growing.
Know which consumers and occasions are driving adoption before you commit.
Walk into leadership approval with explainable evidence, not just a ranked list.
Bring a clear demand rationale into retailer conversations and launch decisions.
Move from concept-ready ideas to decisions backed by commercial evidence.
Tastewise helps teams build evidence and confidence around the concepts that matter most.
AI Palette helps teams produce and screen a larger volume of concepts faster.
AI Palette helps teams determine which concepts deserve further exploration.
Tastewise moves teams from concept evaluation to market-ready decisions backed by explainable evidence and clear commercial rationale.
AI Palette's strength is moving quickly from trend identification to concept development.
Often the answer is both, in sequence. Generate and screen concepts, then validate demand and build the case behind the strongest.
I was checking what was happening with diet trends. Tastewise gave me a clear answer in two clicks. Much faster than anything else we use.
increase in sales conversions for teams using Tastewise sell-in narratives.
See how Tastewise helps teams validate demand, build stronger business cases, and move innovation forward with confidence.
AI Palette helps teams generate and screen concepts. Tastewise helps teams validate demand, build the business case behind concepts, and support commercialization decisions.
Not entirely. AI Palette is focused on concept generation and screening. Tastewise focuses on demand validation, evidence building, and innovation decision support. Many organizations use both at different stages.
Tastewise combines consumer panels, home cooking signals, foodservice activity, retail and eRetail trackers, consumer surveys, and AI agents to explain demand drivers, consumer segments, and growth opportunities.
Both support innovation at different stages. AI Palette accelerates concept generation and prioritization. Tastewise validates demand and builds the evidence needed to move concepts into development and commercialization.
Many teams already have concept generation processes in place. The challenge is proving which concepts deserve investment. Tastewise helps provide the evidence, rationale, and commercial story required to move concepts forward.
Concept screening platforms help evaluate and prioritize ideas. They are less focused on building explainable evidence, supporting retailer conversations, validating demand drivers, and creating activation-ready outputs.