Myntra today outlined the next phase of its technology buildout, anchored by AI capabilities spanning customer discovery, seller onboarding, catalog infrastructure, and how its engineering teams build and ship products. The rollout is built around three core pillars — customer experience, seller enablement, and operational efficiency.

Across each pillar, AI is doing specific, measurable work. For customers, it is powering personalised discovery, size and fit guidance, and creator content at scale. For sellers, it has cut onboarding from 15 days to under 2, giving brands faster access to Myntra's platform and customer base. And internally, it is reshaping how catalog generation is done, how teams run data queries, and build and ship products — compressing timelines that previously took days into hours.

Sharon Pais, Head of Myntra, said, "Technology has always been at the core of every journey on Myntra. Our focus remains on strengthening capabilities that give brand partners clear pathways to scale while continuing to make the shopping experience more relevant and confident for customers.  This consistent approach compounds across thousands of brands and directly shapes how customers discover on the platform. For us, AI is not just a layer we have added on top, it sits at the heart of how Myntra operates, from the moment a customer opens the app to how our teams continue to innovate."

Customer Experience: Personalised Discovery and Confident Purchase Decisions

Beyond Maya, its conversational AI assistant, Myntra is expanding its AI capabilities for fashion discovery beyond product search toward personalised styling. Its AI-led Contextual Styling Suite offers real-time look pairings across the catalog, helping shoppers understand not just what they like but where they can wear it and soon, how to style it as a complete look.

On size and fit — one of the most persistent challenges in online fashion — Myntra has built an AI-powered Size and Fit Intelligence layer that goes beyond size recommendations to explain why a particular size may work for a given shopper, and to visualise how garments may drape across different body types. The size recommendation layer currently covers approximately 85% of the eligible apparel portfolio, with size explainability responses delivered in under two seconds. Fit visualisation across multiple body types is being scaled up and rolling out to users progressively.

To support creator-led discovery at scale, Myntra has deployed an automated content processing layer that uses machine learning models to validate standard formatting and catalog alignment, routing complex reviews to specialist teams. This reduces review timelines while maintaining quality across the platform.

Together, these capabilities build on Myntra's personalisation foundation — 90% of monthly active users experience personalised search on the platform today.

Seller Enablement: Faster Onboarding, Clearer Growth Pathways

The most significant change in this rollout for sellers is in onboarding. Myntra's AI-powered Seller Growth Hub has reduced end-to-end onboarding time from 10-15 days to approximately 1-2 days, with seller registration completing within minutes. Once onboarded, early-stage sellers receive daily operational guidance to progress toward their first set of orders. As sellers scale, they gain access to trend insights, performance dashboards, and growth tools.

Complementing the Seller Growth Hub is Saarthi, Myntra's AI-led voice intelligence platform. Saarthi automates structured partner communications, manages high-volume operational queries, and routes complex issues to specialist human support teams. Internal teams can also build custom use cases on the platform — for example, deploying a voice campaign for a new product launch.

Operational Efficiency: Faster Catalog, Faster Decisions, Faster Product Development

To accelerate market access for brands and sellers, Myntra provides advanced digital cataloging tools that optimise creative asset generation. Myntra's cataloging infrastructure now produces 400-600 dynamic product videos daily, with catalog generation turnaround cut from 1 day to 4 hours. The system maps up to 40 structural attributes per product to support search visibility for independent brands and sellers. Myntra's internal compliance protocol, Scout, applies quality guardrails before publication, with human catalog experts as the final check on listing accuracy.

BIRA, Myntra's Business Intelligence Retrieval Agent, enables internal teams to run complex data queries in everyday language over Myntra's data infrastructure, automatically generating the relevant SQL without requiring deep technical knowledge. Analytical workflows that previously took days now take minutes.  The platform empowers teams to conduct deeper analyses and make proactive, data-backed strategic decisions.

On the product development side, AI has helped drive a 40% increase in feature rollout velocity. AI tools handle routine development, testing, and diagnostic cycles, allowing engineering teams to focus on architecture and system resilience. All platform deployments retain human oversight.

At the supply chain level, the time required to run complex network simulations has been compressed from 2 days to 1 hour. Meera, Myntra's conversational support layer, resolves over 30% of standard customer queries, allowing human support teams to focus on complex cases.

Myntra's AI deployment across all these areas operates with human oversight, privacy safeguards, and governance built into relevant workflows.