AI Garage Sale is an innovative platform where AI salespeople manage the marketplace, offering a unique buying experience. Users can haggle with AI bots to get the best deal on various items, from high-value electronics like PS5 consoles to nostalgic collectibles. This merging of AI technology with traditional shopping haggling creates an engaging and entertaining retail experience. The platform is designed to push the boundaries of e-commerce by integrating AI-driven negotiations, giving users a chance to test their haggling skills against intelligent algorithms.

XianyuAutoAgent integrates OpenAI’s language models to monitor incoming messages from potential buyers on Xianyu, automatically generate context-aware replies, handle price negotiation dialogs, and update item listings. Sellers configure their account credentials and messaging rules, then the agent runs continuously to ensure fast, consistent communication, maximize conversion rates, and free up time for strategic selling activities. It supports multi-account setups, customizable response templates, and can be scheduled for 24/7 operation.

AI Haggler is a web app that handles phone calls to businesses for you. It can inquire about prices, availability, negotiate better deals, and even make appointments. Whether you need a dentist, plumber, or a last-minute hotel booking, AI Haggler’s AI agent makes the calls you avoid, saving you time and possibly securing discounts. You simply choose the task, the AI makes the calls, and you get detailed reports to compare and choose the best options.

negotiation_agent provides a modular toolkit for building autonomous negotiation bots powered by GPT-like models. Developers can specify negotiation scenarios by defining items, preferences, and utility functions to model agent objectives. The framework includes pre-defined agent templates and allows integration of custom strategies, enabling offer generation, counteroffer evaluation, acceptance decisions, and deal closure. It manages dialogue flows using standardized protocols, supports batch simulations for tournament-style experiments, and calculates performance metrics such as agreement rate, utility gains, and fairness scores. The open architecture facilitates swapping underlying LLM backends and extending agent logic through plugins. With negotiation_agent, teams can quickly prototype and evaluate automated bargaining solutions in e-commerce, research, and educational settings.