As AI Agents Start Shopping, Kindred Is Quietly Powering the Infrastructure Behind the Curtain
by on 2nd May 2025 in News
With OpenAI now weaving native shopping into ChatGPT, the landscape of digital commerce is entering a new phase. We’re moving beyond search and recommendation into a world where AI agents can take real transactional steps on our behalf—finding deals, comparing prices, and completing purchases autonomously.
What these agents need isn’t another affiliate program or scraped price feed. They need a reliable, open foundation of live, executable commerce data. That’s where Kindred steps in.
Kindred has just launched the Global Merchant dataset—an open dataset specifically designed to help LLMs and AI agents drive real-world commerce. It includes over 4 million fully-qualified deal links and data on more than 100,000 merchants, structured for fast retrieval, embedding, and link execution.
It’s already live and available at:
• github.com/kindred-io/global-merchant-dataset
•huggingface.co/kindred/global-merchant-dataset
Every product link in the dataset is active, monetisable, and structured to work across agents, chatbots, personal shopping tools, and autonomous AI interfaces. Whether you’re building a consumer assistant, a voice interface, or an agent-to-agent commerce layer, Kindred provides the raw infrastructure for transactional intelligence.
The dataset is RAG-ready, meaning developers can feed it directly into retrieval-augmented generation workflows or plug it into vector databases for scalable similarity search. Each merchant and product is linkable, navigable, and designed to convert.
As LLMs begin to act on behalf of users—not just suggest, but transact—the need for clean, open, and monetizable merchant data becomes foundational. That’s the role Kindred is already playing.
We’re not trying to be the storefront. We’re making it possible for any AI to build one.
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