ZILO raises $15.3M to scale 60-minute fashion

Fashion quick-commerce startup ZILO has secured fresh Series A funding to scale its 60-minute apparel delivery model, deepen its tech stack, and expand beyond Mumbai over the next year. This development also fits a broader commerce-tech narrative that the ai world organisation regularly tracks through the ai world summit, ai world organisation events, and other ai conferences by ai world.

Funding that signals a bigger ambition

ZILO has raised $15.3 million (Rs 140 crore) in a Series A round led by Peak XV Partners, with Peak XV investing $8 million as the lead cheque. Existing backers InfoEdge Ventures and Chiratae Ventures also joined the round with $2.5 million each, reinforcing continuity in investor conviction as ZILO moves from early traction to scale mode.

Alongside the core VC participation, the round included debt-focused and venture lending participation from Alteria Capital and Stride Ventures, a structure that often helps consumer logistics businesses balance growth spending with tighter cash discipline. The cap table also expands with a set of well-known angel investors, including Lalit Keshre (Groww), Kunal Shah (CRED), Sachin Oswal, Ayyappan R, Abhishek Bansal, Sreevathsa Prabhakar, and Preeta Sukhtankar.

What makes this round notable is not only the amount, but the problem ZILO is choosing to solve: fashion discovery, trial, and returns are traditionally “slow-commerce” behaviors, yet ZILO is attempting to compress them into quick-commerce timelines. As the ai world organisation frames it in many of its conversations around retail tech and last-mile innovation, the next wave of consumer platforms will be defined by how well they blend speed with personalization, service quality, and supply-chain predictability—topics that naturally surface at the ai world summit and across ai conferences by ai world.

Who invested, and what the round is for

ZILO’s stated use of proceeds is clear: scale operations, invest in technology, expand into new markets, and strengthen the supply chain so the model can hold up as demand and SKU breadth increase. Today, the company operates in Mumbai, and it plans to expand to additional cities over the next 12–14 months, which implies a fairly aggressive rollout cadence if it targets multiple metros and high-density urban clusters.

This Series A follows ZILO’s earlier seed raise of $4.5 million in June last year, which was led by Info Edge Ventures and Chiratae Ventures, giving context to how quickly the company has moved from seed to a larger institutional round. In fast-moving categories like quick commerce, that timeline often reflects early proof on repeat behavior, delivery reliability, and unit economics assumptions—especially critical in fashion where returns and size swaps can erase margin.

The investor mix also hints at what ZILO will likely prioritize next: operational scale to support more pin codes, stronger supply systems to reduce stock-outs, and product/engineering work that can improve catalog relevance and reduce return friction. For readers following the ai world summit 2025 / 2026 programming themes, this is a real-world case study in how consumer-facing speed is increasingly “manufactured” by backend decisions—inventory placement, routing logic, and data-led demand forecasting—rather than by marketing claims alone.

In practical terms, strengthening the supply chain for a 60-minute apparel promise is less about adding more riders and more about ensuring the right items are pre-positioned, the catalog is accurate, and the returns workflow doesn’t clog fulfillment capacity. This is exactly where modern AI-enabled planning, warehouse optimization, and customer support automation can become competitive moats—areas that the ai world organisation community tends to explore via ai world organisation events and industry meetups.

How ZILO’s 60-minute fashion model works

ZILO is positioned as a fashion quick-commerce platform delivering apparel within 60 minutes, which is an operational promise that forces the company to think differently about assortment design, inventory control, and service steps. The startup was co-founded by Padmakumar Pal and Bhavik Jhaveri, both former Flipkart and Myntra executives, suggesting the founding team has deep exposure to Indian e-commerce execution and fashion category dynamics.

A key part of the offer is that ZILO works with more than 200 brands, indicating the platform is aiming for breadth in labels rather than operating as a narrow private-label-only play. On top of speed, it also advertises service-layer features such as home trials and instant returns, which—if executed consistently—can reduce a shopper’s hesitation to buy fashion without touching or trying the product.

To make 60-minute delivery feasible, ZILO follows a vertically integrated model combining dark stores and brand outlets to manage inventory and delivery timelines. That hybrid approach matters because fashion inventory is fragmented across sizes, colors, and styles, so relying purely on a single warehouse format can increase missed deliveries, substitutions, or cancellations when demand spikes.

From a customer-experience perspective, the bet is that “speed + trial + easy returns” can shift fashion from planned shopping to impulse-friendly shopping without destroying trust. For the ai world summit audience, this kind of model is an example of how service design (trials, returns, reliability) increasingly differentiates consumer apps as much as price does, and why AI-driven operations are becoming central to quick-commerce category expansion.

Expansion roadmap: cities, tech, and supply chain

ZILO’s immediate expansion plan is to move beyond Mumbai into additional cities within 12–14 months, which typically requires replicable playbooks for onboarding brands, securing local inventory nodes, and hiring operations teams that can maintain delivery SLAs. Because the proceeds are also earmarked for technology investment, expect efforts that improve catalog intelligence, demand prediction by micro-market, and tighter orchestration between dark stores and partner brand outlets.

Scaling operations in this category is rarely linear: adding cities increases complexity not only in routing and rider density, but also in fashion-specific issues like size availability, style seasonality, and higher customer expectations for presentation quality. Strengthening the supply chain, as the company has stated, is therefore not a generic objective—it is the backbone that determines whether 60-minute fashion remains a premium promise or becomes an expensive liability.

It also helps to view this roadmap against ZILO’s funding history: after raising $4.5 million in seed in June last year, moving to a $15.3 million Series A suggests the company is now optimizing for scale and defensibility rather than just experimentation. That arc—prove a sharp wedge in one city, then expand with better tooling and stronger operational controls—shows up repeatedly in high-growth consumer-tech stories discussed at the ai world organisation ecosystem, including the ai world summit.

For teams inside the ai world organisation and its broader community, the operational questions ZILO now faces are the same ones that define next-gen commerce winners: how to reduce return costs without adding friction, how to keep fulfillment accuracy high while increasing SKU count, and how to use tech to standardize decisions across cities. These are also precisely the kinds of discussions that fit well into ai world organisation events and panels at ai conferences by ai world, where practitioners compare what scales in the real world versus what only looks good in pitch decks.

Competitive landscape and why this round matters

ZILO is not alone in chasing fast fashion delivery: the broader space includes other quick-commerce fashion platforms as well as incumbent e-commerce players experimenting with faster fulfillment. A recent example mentioned in the same context is Mumbai-based quick-commerce fashion platform KNOT, which raised $5 million in a funding round led by 12 Flags, highlighting continued investor appetite for “fast fashion, fast delivery” variations.

The competitive set also includes Slikk and Myntra, with Myntra expanding its quick fashion delivery offering to additional cities, which raises the bar because incumbents can leverage brand relationships, traffic, and logistics experience. In that environment, ZILO’s differentiation will likely depend on how reliably it can deliver in 60 minutes, how smooth home trials and instant returns feel in practice, and how effectively it can balance inventory breadth with utilization.

This is where the funding becomes strategically important: capital can buy time to refine operations, build technology, and expand supply nodes before a larger player’s rollout or a competitor’s city expansion compresses the whitespace. If ZILO executes well, it may help redefine consumer expectations around how quickly fashion can be accessed in urban India—an evolution that commerce, AI, and logistics leaders will likely track closely as part of ai world summit 2025 / 2026 conversations.

From the ai world organisation lens, this story is bigger than one funding headline because it shows how category boundaries are dissolving: “quick commerce” is no longer just groceries and daily essentials, and “fashion commerce” is no longer confined to next-day delivery. As the ai world summit continues to convene builders and operators across AI, product, and supply chains, cases like ZILO offer practical lessons on how technology and operational design can compress time-to-value for consumers while staying commercially viable.

Finally, this trend creates new partnership and innovation opportunities—from predictive sizing and personalization to inventory rebalancing and automated returns triage—each of which can be explored through the ai world organisation, its ai world organisation events calendar, and the broader slate of ai conferences by ai world. For readers tracking India’s startup ecosystem, ZILO’s Series A is an indicator that investors still believe in consumer-speed propositions, provided the company can engineer the backend to make the promise profitable.