Faster Fashion — Using AI to Accelerate Speed to Market: In Conversation with Jade Huang

Jade Huang, co-founder and CEO, StyleSage

In this series, we talk with the amazing founders who are part of the SAP.iO Foundry in New York — Women-led Enterprise Tech Program. This 16-week program, launched April 18th, provides access to tailored mentorship, exposure to SAP technologies, and opportunities to meet with SAP customers, to help these incredible startups scale. SAP.iO Foundries are in major startup hubs, including Berlin, Tel Aviv, New York City, San Francisco, and Paris.

Jade Huang’s journey in enterprise technology was rather serendipitous. From aspiring fashion designer to self-taught programmer, she is now the founder and CEO of StyleSage, part of the SAP.iO Foundry in New York. StyleSage is an AI-powered retail analytics solution that enables brands to increase their speed to market, with real-time insights across 4 key business areas: Pricing, Assortment, Promotions, and Trends. Leveraging its differentiating image recognition capabilities, StyleSage also powers rapid processing for several key eCommerce backend capabilities, to help their customers get products in front of consumers faster than ever.


  1. Let’s talk about your journey as an entrepreneur. What inspired you to start StyleSage?

I went to business school in France at INSEAD, where I was inspired by a business case on Zara and how they achieved global success through their agile processes and discipline to ingest analytics. The idea was to build software that grants the same data access to brands and retailers, so that the industry can move faster as a whole to meet consumer demand.

From my days studying fashion design at Parsons School of Design, I knew that we could solve a number of bottlenecks with the right analytics and technology. We went out and talked to actual veterans of the industry to really understand what kept them up at night, what were difficult for their teams, and what was distracting them and diluting their focus. And that’s how this idea came about: to automate a lot of processes that their teams were having to do manually, so they could focus on what they do best: creating really beautiful garments that people want to wear.

2) What was your previous experience in Enterprise tech and how did it prepare you for the role?

My involvement with technology is one of serendipity. When I first moved to New York as a teenager, I studied Fashion Design at Parsons School of Design and, to be completely honest, I prized partying over going to school, which meant I lost my scholarship and flunked out — much to my parents’ shame — and accidentally found myself involved in technology. I became a digital designer, then user experience designer, and taught myself programming. So I was actually in tech for about 10 years before starting this company out of business school.

Before business school, I worked for the government under the Obama Administration. I was part of an innovation team that was charged with modernizing and optimizing the government with tech — a bit like a parallel universe to what I am doing now. In that role, I was exposed to the sheer scale of what our tech had to serve and, understood that what constituted an MVP (minimum viable product) in enterprise tech is very different from that of consumer tech. That’s why during the first two years of the company, we invested a ton of engineering into the backbone of our tech — this is why we are faster than any of our competitors in the market — we had built up the capacity to scale since the first day.

3) Analytics is becoming all the more important, given the availability of an incredible amount of data. Employing AI to do the heavy lifting, how do you think it’s impacting Enterprise tech now — and do you think companies are keeping pace?

Analytics and tracking metrics are of course important. I think almost everyone is in agreement that AI can automate a lot of tedious, manual processes that no human wants to take on. In our work with clients, we’ve found that it’s actually not a question of whether to employ AI but whether your organization has the right processes and capacity set up to incorporate AI. Does your team have the skillset to merge AI into current processes? Do your current processes need to be completely overhauled because the nature of how you interact with your customers have changed? Is there a team who is monitoring the performance to AI and tweaking it according to the feedback it’s looping back? And organizationally readiness to leverage AI in critical processes and decisions varies greatly from company to company.

4) As a founder, what do you think have been the most challenging aspects of building an Enterprise tech startup?

Building the right team and the right culture. The profiles and people you need when your company has just three employees versus who you need when the company grows to more than even 10 or 15 are completely different. As founders, we try our best to motivate our teams in the right direction while motivating ourselves. In an early stage startup like ours, the peaks and valleys are huge — so it’s important to keep yourselves and your teams focused.

5) What advice would you have for other women entrepreneurs out there who are thinking about venturing out on their own?

Talk to as many people as possible. I think sometimes people feel shy about talking about their ideas. But without sharing and receiving feedback, you are potentially missing out on critical ideas and information that would help you build your business.

When I first started, I talked to as many classmates who came from consulting as possible. These classmates are 1) smart, 2) analytical, and 3) trained to find as many things wrong with my idea as possible. They identified so many gaps in my initial idea — and each time that happened, I would do my homework and talk to as many people relevant to those gaps as possible. For example, if they identified a gap in how I am thinking about marketing, then I would talk to people whose specialty was marketing to understand how I might address those gaps.

6) As a parting shot, what’s your favorite part of being in the SAP.iO Foundry in New York?

What we do at StyleSage aligns very well with SAP’s Intelligent Enterprise strategy, particularly with SAP’s eCommerce-focused Customer Experience solutions. For instance, our Competitive Intelligence tool could help customers by providing quick access to market intelligence and potentially also automate product suggestions. Being part of the Foundry, we are able to find the right kind of people and get the right kind of advice as we find ways of working with SAP — that’s just the sort of support we needed.

Through the program, we have also been able to meet SAP retail industry customers who have all been very responsive to StyleSage, so this really is an affirmation of what we are doing.

Lastly, being a part of a community with so many admirable female CEOs and founders has been amazing. I find them incredibly inspiring and that pushes me to try harder. There aren’t that many women in enterprise tech, so this support network is invaluable, whether it is to talk through challenges in scaling the team, fundraising, or to motivate each other.