The way formulators discover ingredients is evolving. While early-stage research increasingly begins in conversational AI tools, product evaluation, technical validation and supplier selection still require trusted, industry-specific information. LTRUS® Prospector® AI Search was designed to bring conversational research directly into the supplier-validated environment where those decisions already take place.
For suppliers, this creates both an opportunity and a responsibility. The quality of your product data now plays an even larger role in whether your ingredients are surfaced when formulators ask questions.
How the new Prospector AI Search evaluates products
When a user submits a query, Prospector AI Search breaks the request into multiple dimensions, including:
- Intended application
- Functional requirements
- System compatibility
- Regulatory and certification requirements
- Sensory and performance characteristics
For example, a formulator may search for an emulsifier suitable for a leave-on facial moisturizer that meets specific certification and stability requirements. The AI interprets those conditions, identifies matching products, evaluates available documentation, and ranks results according to relevance and confidence.
Why certain products surface first
Product rankings are influenced by three primary signals:
- Direct attribute match – Products with attributes that directly align to the request receive the strongest ranking signal.
- Chemical reasoning – If chemistry suggests a product may be suitable even though a use case isn’t explicitly stated, the AI can identify a potential match, but those recommendations are ranked lower than direct matches.
- Product availability – Active products receive priority over discontinued or discretionary offerings.
Where to focus first: Four high-impact optimization priorities
While suppliers don’t need to optimize everything at once, :
- Complete your INCI information – International Nomenclature of Cosmetic Ingredients (INCI) names remain one of the most common pathways formulators use to identify ingredient options. Products lacking this information have a significant discoverability disadvantage.
- Expand functionality tags – Many searches begin with a functional need rather than a product name. Capture all relevant functions to maximize matching opportunities.
- Add detailed application tags – Clearly indicate intended end-use markets and applications. Application context helps AI better align products with formulation goals.
- Include use levels – Use level information is among the most valuable data points for formulators evaluating alternatives. Even estimated ranges help improve discoverability.
The bottom line
Prospector AI Search is designed to connect formulators with trusted, supplier-validated ingredient information. The more complete, structured and documented your listing is, the greater the likelihood that your products will be surfaced when buyers are actively evaluating solutions.
The goal isn’t simply to have a listing. It’s to create a listing that clearly communicates your product’s properties, applications, claims and supporting documentation in the format the
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