Netcore Unbxd’s Agentic multimodal introduces a unified approach that allows shoppers to upload an image and refine it with language prompts.
Netcore Unbxd, a provider of AI-powered product discovery tools, announced the launch of its Agentic Multimodal Search capability, designed to help ecommerce systems interpret shopper intent by processing images alongside natural language input, whether typed or voice-enabled, within a single search experience.
The launch reflects a broader shift underway in digital commerce: search is no longer a retrieval problem. It is an interpretive intent problem, increasingly mediated by AI systems rather than by explicit human input.
“As commerce becomes more visual and AI-led, shoppers shouldn’t have to translate intent into rigid search terms,” said Ravi Shankar Mishra, Product and Conversational Director at Netcore Unbxd. “Agentic multimodal search allows the teams to understand how shoppers see products and how they describe them, combining visual cues with language-based refinement in real-time.”
Traditional ecommerce search systems have largely treated image search and text search as separate workflows. In practice, shoppers combine visual input with descriptive context, referencing style, colour, material, or price preferences together. Netcore Unbxd’s agentic multimodal capability uses a unified approach that allows shoppers to upload an image and refine it with language prompts.
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Rather than processing inputs independently, the system evaluates visual and language signals together to form a combined understanding of shopper intent. Visual inputs provide aesthetic context, while language introduces constraints and preferences.
Results are then ranked using product popularity, user behaviour, geo-location, freshness, semantic understanding, and relevance signals. This combined approach is useful for visually driven categories such as fashion, furniture, home decor, jewellery, and lifestyle products, where aesthetics can influence discovery as much as specifications.
As AI adoption increases, the limitation is less about intelligence and more about how systems translate imperfect input into practical outcomes. The architectural change is that relevance moves from string matching to meaning matching, and from static rules to more adaptive reasoning.
“Visual search answers what looks similar,” said Nishant Jain, COO, Netcore Unbxd. “Agentic multimodal search enables retailers to surface what aligns with the shopper’s intent by understanding both visual inspiration and descriptive context together.”
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Multimodal search is increasingly being used as part of a broader agentic commerce stack, where AI systems are expected to go beyond recommendations and take actions within defined boundaries.
Three factors are contributing to this shift globally:
- Mobile-first behaviour, where cameras are often the fastest way to begin a search
- Visually differentiated catalogues, where aesthetics influence choice more than specifications
- Rising AI expectations, with shoppers expecting systems to interpret intent across multiple forms of input
In this context, search is one of the first customer-facing systems to move from passive retrieval to more active interpretation and execution.
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Retailers using agentic multimodal search can improve discovery across inspiration-led journeys, long-tail queries, and exploratory browsing. By enabling systems to interpret intent across multiple modalities, ecommerce teams can provide more relevant product discovery when input is partial or mainly visual.
The system is also designed to be resilient, continuing to perform when shopper input is vague or catalogue data is incomplete.
Netcore Unbxd is positioning agentic, multimodal search as a foundational capability in modern ecommerce infrastructure, enabling retailers to support both traditional search behaviour and emerging AI-assisted shopping experiences.
“Search is becoming the first agent in the commerce stack,” added Nishant Arora, Senior Vice President of Marketing at Netcore. “The ability to understand visual and language intent together is becoming essential as commerce experiences grow more dynamic and AI-enabled.”
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