PredictSys is raising a Crowd SAFE at a $10 million valuation, or $8 million valuation for early bird investors. PredictSys was founded in 2019, and has only produced a minimum viable product (MVP) thus far. As such, the company has not generated any revenue, and seems to be a ways away from entering the market. With this little proof of traction, a $10 million valuation is high. As a result, PredictSys’ price rating is low. 

PredictSys will license its software to fashion brands that will merge in-house merchandising data with PredictSys’ proprietary data platform to receive product-level insights on how much to buy, what to price, and more. As such, PredictSys is a B2B company selling to fashion brands, and likely only medium- to large-sized fashion brands that can afford to think deeply about the inventory decisions behind each SKU. PredictSys’ potential clients likely number in the hundreds, or perhaps the low thousands; the company’s potential is constrained by the actual quantity of successful brands in the fashion industry. 

That being said, PredictSys will have a license to charge a premium for its product, if the MVP works properly during beta testing. H&M alone produced $4.3 billion worth of excess inventory in 2018, so theoretically brands are willing to pay a large amount to shrink that massive waste of cash. PredictSys’ presumably high price point counters its niche market size somewhat, but the company’s market rating is not remarkable.

PredictSys was founded by Abhinav Chandra, who has over a decade of experience in the retail industry. After receiving dual MBAs from London Business School and the Stephen M. Ross School of Business at the University of Michigan, Chandra went to work for McKinsey, where he ultimately served as an Associate Partner. After seven years at McKinsey, Chandra began working at Amazon, where he served as a “Senior Leader” in the women’s clothing department and ultimately as the Head of Customer Experience. 

Chandra’s colleagues Andy Nguyen (Head of Sales) and Bobby Malik (CTO) can’t be found on LinkedIn (they might only be working part-time for PredictSys), but they also apparently have backgrounds in fashion retail. 

Chandra’s background is ideal for managing a retail business that intersects with major fashion brands; he has experience working in a fashion department at Amazon, and has prestigious business credentials from McKinsey. PredictSys would likely benefit from an involved technical co-founder, given that the company’s success is heavily dependent on the strength of its technology; that slight drawback reduces PredictSys’ team score to middle-of-the-road. 

While it’s difficult to fully assess PredictSys’ competitive advantages before the full product is live, it does seem as though PredictSys has captured a strong idea that has the potential to be very valuable for fashion brands. It’s unlikely that brands would have the capability to combine their data with a significant number of outside data sources and process that data intelligently to produce product-level insights. It also seems as though PredictSys will have a strong defensibility moat if its product can indeed function as intended. While the market is somewhat niche, PredictSys has the potential to become a market leader with highly differentiated technology; thus, the company’s differentiation score is moderately high. 

PredictSys is pre-revenue, and only 2019 financials are available for review; as a result, there is virtually no data on PredictSys’ performance to evaluate. We do know that the company posted a net loss of just over $50,000 in 2019, its first year in existence; it’s not clear how much cash the company burned in 2020, when product development theoretically ramped up. PredictSys hasn’t generated any other performance metrics yet, so the company’s performance rating is the lowest possible. 

The biggest reason to be pessimistic about PredictSys is a simple lack of data. The company is really only a concept at this point, with no actual beta results or performance history to evaluate. Thus, investors at this stage have to trust the high-level concept of PredictSys. While that concept does seem to be a sound one, an investment in a pre-revenue, pre-beta company is a level of risk far beyond even the typical riskiness of startup investing.

While PredictSys is still very young, and it’s too soon to say whether the company can be successful, there are positive signals that PredictSys has potential. First of all, the company’s founder does have impressive business and fashion retail credentials from McKinsey and Amazon. In addition, it seems that PredictSys has the potential to be strongly differentiated from less functional fashion technology companies, and could quickly dominate the market if its product proves successful. While these facts aren’t very much to go on, PredictSys does seem to be solving an urgent, concerning problem for potential buyers, and seems to be doing so in a way that makes sense. While an investment in PredictSys is a bit of a gamble at this stage, it’s a gamble that just might pay off. 

PredictSys is a pre-revenue fashion technology startup developing technology to help fashion brands plan inventory to reduce waste. The company’s artificial intelligence-enabled software will blend fashion brands’ in-house data with 100+ outside data sources to help predict demand for clothes at an SKU level, hopefully reducing fashion brands’ enormous, climate-damaging overstock. PredictSys was founded by a credible fashion business leader, and seems to be making progress toward testing an MVP that could deliver real value to its customers. 

On the other hand, it’s really just too soon to say whether PredictSys can achieve success. The company has been around for two years, and hasn’t yet generated revenue; though the concept seems promising, it’s difficult to judge whether the product is actually effective without some beta test data or testimonials from early customers. Therefore, PredictSys has been rated a Neutral Deal. 

For questions regarding the KingsCrowd staff pick or ratings for this company, please reach out to support@kingscrowd.com.