The discovery layer that helps buyers in high-consideration categories build a preference by reacting to real products, turning vague intent into a confident, high-value decision.
In complex, high-consideration purchases (real estate, travel, automotive, hospitality, wholesale, manufacturing, big-ticket equipment), most buyers do not arrive knowing what they want.
Conversational search cannot rescue them. It only executes a preference the buyer already holds, so a raw catalog behind a chat box is slower than filters for the decided and useless for the undecided.
The Kleio Agentic Discovery Engine helps the buyer build their preference instead of waiting for it. The buyer reacts to real products; the engine learns from every reaction, revises what it believes, and sharpens the next recommendation.
Preferences are constructed during the decision, not retrieved from memory.
Agentic discovery builds the intent that search assumes. Buyers react to real options instead of stating specs. Each reaction sharpens the probabilistic Memory Store.
Presents real products to react to and learns from each reaction.
Wins the weak-intent majority, not just the decided tail.
Beliefs are added, revised, or erased with a confidence score.
Recommendations track the buyer as their thinking shifts.
Seeded from CRM and segments; every belief tagged prior, chat, or reaction.
Personalization from turn one, and an auditable profile.
Hard parameters and soft signals held in one profile.
Reads intent a filter cannot express.
The catalog exposes its parameter space; a rejection re-queries it.
Grounded recommendations and graceful recovery from a no.
Every memory and query change is recorded.
Trust, tuning, and compliance across the journey.
Search assumes the answer exists and just waits to be found. Discovery assumes it must be built. The engine's edge is the objective (construct intent, not recall it) and the coupling to your live catalog.
