Netcore Unbxd Launches Agentic Multimodal Search to Enable E-commerce to Interpret Visual and Language Intent in a Single Experience

New capability unifies image and language understanding, including text and voice-enabled queries, enabling retailers to interpret intent even when spoken queries differ from written ones through conversational phrasing, phonetic variations, or transliterated terms, allowing teams to move beyond isolated inputs toward intent-aware product discovery.

MUMBAI, India, March 30, 2026 /PRNewswire/ -- Netcore Unbxd, a leading provider of AI-powered product discovery solutions, today announced the global launch of its Agentic Multimodal Search capability, designed to help e-commerce systems interpret shopper intent by understanding 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 e-commerce search systems have largely treated image search and text search as separate workflows. In practice, shoppers combine visual inspiration with descriptive context, referencing style, colour, material, or price preferences together. Netcore Unbxd's Agentic multimodal introduces a unified approach that allows shoppers to upload an image and refine it with language prompts.

Rather than processing inputs independently, the system evaluates visual signals and language signals together to form a cohesive understanding of shopper intent. Visual inputs anchor aesthetic context, while language introduces constraints and preferences. Results are then ranked using a combination of product popularity, user behaviour, geo-location, freshness, semantic understanding, and relevance signals.

This unified approach is particularly valuable for visually driven categories such as fashion, furniture, home decor, jewellery, and lifestyle products, where aesthetics often influence discovery as much as specifications.

As AI adoption accelerates, the limitation is no longer intelligence, but execution on how systems translate imperfect input into meaningful outcomes.

The architectural shift is subtle but important: relevance moves from string matching to meaning matching, and from static rules to agentic 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."

Multimodal search is increasingly being adopted as part of a broader agentic commerce stack, where AI systems are expected to move beyond recommendations and take accountable actions within defined boundaries.

Three forces are accelerating this shift globally:

• Mobile-first behaviour, where cameras are often the fastest way to begin a search
• Visually differentiated catalogues, where aesthetics drive choice more than specifications
• Rising AI expectations, with shoppers expecting systems to understand intent across multiple forms of input

In this environment, search becomes one of the first customer-facing systems to evolve from passive retrieval to active interpretation and execution.

Retailers adopting agentic multimodal search can strengthen discovery across inspiration-led journeys, long-tail queries, and exploratory browsing experiences. By enabling systems to interpret intent across multiple modalities, e-commerce teams can deliver more relevant product discovery when input is partial or highly visual.

More importantly, the system increases resilience, continuing to perform even when shopper input is vague or catalogue data is incomplete.

Netcore Unbxd is positioning agentic, multimodal search as a foundational capability in modern e-commerce 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 (SVP) 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."

About Netcore Unbxd

Netcore Unbxd is an AI-powered product discovery platform that helps brands provide personalized customer experiences to scale online exponentially. Our commitment to revolutionizing e-commerce experiences has garnered us esteemed recognition, positioning us as a leader in Gartner® 2024 Magic Quadrant™ for Search and Discovery and the Forrester Wave™ : Commerce Search and Product Discovery, Q3 2023 report.

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