Lily AI helps brands make product content more machine-readable.
Novi goes deeper by identifying which attributes, evidence, and authority signals actually influence whether a product gets selected and recommended.
Making product content machine-readable is only the first step. Novi identifies which attributes, evidence, and authority signals actually influence selection, ranking, and recommendation.
What stood out most was how clearly Novi connected structured product data, trust signals, and verification to real AI visibility and recommendations.
We’ve always aimed to stay ahead of the curve — bringing household consumables to ecommerce early and pioneering biobased cleaning for over 30 years. Partnering with Novi is a natural next step, helping ensure Dropps is represented clearly and accurately in AI-driven shopping experiences.
Lily AI focuses on making product information richer, more structured, and easier for machines to understand. Novi focuses on understanding what actually drives product selection and recommendation, including which attributes and authority signals matter most within a category.
Novi measures whether products are actually being recalled, selected, ranked, and recommended, then identifies the signals influencing those outcomes. The goal is not only to make content readable, but to understand what makes a product competitive for recommendation.
AI can understand a product without ultimately choosing it. Novi helps brands understand the additional signals that influence selection and ranking, including category relevance, product evidence, competitive differentiation, and authority.
Yes. Novi translates recommendation intelligence into prioritized changes across product data, PDPs, structured data, content, authority signals, and distribution. The difference is that those changes are guided by what actually influences recommendation performance.
