FERMÀT Launches AI Search Commerce Engine for Retail Brands

Nov 21, 2025
FERMÀT has introduced an AI Search Commerce Engine designed to help retail brands track and convert product visibility across AI platforms like ChatGPT, Claude, and Gemini. The platform generates shoppable, brand-owned content optimized for AI-driven discovery and offers a six-month free trial for early adopters.

FERMÀT has launched its AI Search Commerce Engine, a platform built to help retail brands measure visibility, generate shoppable content, and drive conversions from AI-powered answer tools such as ChatGPT, Claude by Anthropic, and Gemini, announced in a press release.

The system allows brands to monitor high-value AI prompts, automatically generate first-party content tailored to natural language queries, and track engagement through citation-level attribution and competitor benchmarking. It is built using structured data standards like JSON-LD schema markup and has been tested for visibility optimization across major AI platforms.

Early adopters have reported increases in product category visibility and direct conversions from FERMÀT-generated content cited by AI models. To promote adoption, the company is offering six months of free access to qualifying brands, including prompt tracking, generation of up to 20 pieces of shoppable content, and visibility monitoring across supported AI systems.

We hope you enjoyed this article

Consider subscribing to one of our newsletters like Sales & Marketing AI Weekly or Daily AI Brief.

Also, consider following us on social media:

Free newsletter

Sales & Marketing AI Weekly

News about AI tools and innovations for Sales and Marketing professionals.

Whitepaper

Tensordyne Napier: What If One Rack Could Do the Work of Nine?

Tensordyne

This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.

Read more
Free, six days a week

Daily AI Brief: the AI news that matters, in your inbox.