Funding will support an integrated AI platform for product discovery, shopping assistance, customer operations, catalog enrichment, and virtual try-on

Loops has raised $3.5 million in seed funding from a16z speedrun, NTT Docomo, Connecticut Innovations, Alumni Ventures, and Monday Capital to expand its AI-powered commerce platform for brands and retailers.

The platform brings together AI search, product discovery, shopping assistance, customer service, product data enrichment, and virtual try-on in a unified system. The company plans to use the funding to accelerate product development, expand customer deployment capacity, and support international growth.

Loops aims to help retailers connect these functions through shared product knowledge and business context, rather than requiring them to deploy and integrate separate AI tools for individual workflows.

Connecting the Ecommerce Shopping Journey

Many ecommerce platforms rely on separate systems for search, product recommendations, customer support, and product information management. Loops is designed to connect these capabilities so that insights from one interaction can improve the rest of the shopping journey.

Shoppers can describe what they want using natural language, receive relevant product recommendations, and ask follow-up questions through an integrated shopping assistant. The system can also support service conversations across connected channels.

Ilker Selim Zorluoglu, president and co-founder of Loops, said retailers need AI systems that understand their product catalogs, business context, and customer needs rather than a collection of disconnected features.

The company believes this integrated approach can improve product discovery, help shoppers make decisions, and give retailers a more consistent view of customer interactions.

Combining Search, Product Intelligence and Virtual Try-On

Loops connects several AI capabilities within a shared platform:

• AI-powered search and discovery: Shoppers can describe products, styles, occasions, or requirements in natural language without relying solely on keywords and filters.

• Shopping assistance and customer operations: AI assistants answer questions, support purchasing decisions, and manage service conversations across connected channels.

• Product enrichment: The platform improves product descriptions, attributes, and catalog data to make information more useful to shoppers and AI systems.

• Virtual try-on: Shoppers can preview products on themselves, helping bridge the gap between browsing and purchasing.

According to Loops, improvements to product data can strengthen search and recommendation quality, while customer conversations can reveal gaps in catalog information. The company says these feedback loops help its different capabilities improve together.

Retail Deployments Show Early Results

Loops reports that it has more than 70 customers and pilots and has handled millions of shopper experiences. The company also says 64% of its pilots have converted into paying customers.

Turkish supermarket chain A101 uses the platform to help customers navigate its product catalog and receive assistance throughout the shopping journey. In a comparison published by Loops, sessions involving the platform recorded approximately 83% higher observed purchase conversion than the comparison segment. The company notes that this was an observational result, not a randomized experiment.

Fashion retailer Mavi uses Loops for AI-powered search and shopping assistance, allowing customers to explore products by style, occasion, and fit. Its shopping assistant can also provide size recommendations.

Fareed Mosavat, investment partner at a16z speedrun, said commerce offers a clear environment for evaluating the business impact of AI experiences. He pointed to Loops' pilot conversion and early customer expansion as indicators of demand for platforms that support more of the customer journey.

From Ecommerce to Industry-Specific AI

Loops originated after co-founders Ari Nazir and İlker Selim Zorluoğlu encountered a delayed response while trying to purchase a gift online. The experience prompted them to explore how natural-language AI could make product discovery and customer assistance more responsive.

Nazir built an initial prototype over a weekend, which developed into the company's current platform.

Looking ahead, Loops plans to apply its approach beyond ecommerce. The company identifies financial services and energy as potential next markets and is developing specialized small language model capabilities for tasks where domain expertise and deployment requirements favor more focused models.

Its broader strategy is to build industry-specific AI systems that combine domain knowledge, integrations, agents, and controls to support real business workflows. Commerce is the company's initial market, with further expansion intended to bring the same integrated approach to other industries.