One of the key challenges we aimed to address with Ayika was transparent pricing. On many service-based platforms, price negotiation between customers and providers is either rigid (fixed pricing) or manual, involving lengthy back-and-forth discussions that create friction, delays, and user dissatisfaction.
To solve this, I researched and developed an AI/ML-powered adaptive price negotiation system that dynamically adjusts pricing based on market trends, platform demand, and user preferences. This system generates automated counteroffers, ensuring fair, real-time pricing while minimizing negotiation delays.
Each participant in the negotiation process provides a pricing configuration, which is used to automatically create an intelligent agent that acts on their behalf. These agents adjust prices based on:
- Market Trends & Demand – Prices fluctuate based on historical and real-time data.
- User Preferences & Provider Thresholds – Ensures fair offers within predefined margins.
- Automated Counteroffers – Optimizes negotiation by suggesting ideal price points.
These agents also provide a way for users to manually override the automatic negotiation by submitting their own price.
This system eliminates unnecessary delays, improves pricing fairness, and enhances user satisfaction by enabling real-time, data-driven price adjustments.