Domain Intelligence
Most AI platforms are trained to sound smart. Domain intelligence is about being right in the real operating context of CPG. That means understanding how decisions are actually made across brands, retailers, categories, and functions—not how they look in theory.
Our agents are grounded in real-world CPG mechanics: how trade spend works, how retailers behave, where data breaks, and why plans drift once they hit execution. This context allows agents to produce outputs that reflect how the business truly runs, not how a textbook says it should.
- Built on real CPG workflows: planning, forecasting, trade promotion, assortment, item setup, claims, and performance reporting.
- Retailer-aware by default: agents account for how different customers operate, negotiate, and enforce rules—because that’s where theory breaks.
- Function-specific context: category, sales, finance, supply chain, and quality teams see the same problem differently—and the agents respect that.
- Operational realism: assumptions reflect data latency, imperfect inputs, competing priorities, and time pressure.
- Experience encoded: best practices, edge cases, and “things you only learn by doing” are embedded into agent behavior.
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