Standard Cognition

Overview

Standard Cognition is an AI computer vision startup developing technology for physical retail stores. The center of their offering today is cashierless checkout in a retail store, very much competing with the Amazon Go store. Standard Cognition acts as a third party provider to existing retail chains who license their technology and hardware for their stores. A number of chains will be implementing their technology in test stores by the end of 2019. For testing the company also has its own retail store in downtown San Francisco that consumers can use.

Interestingly enough the company claims not to use (or need) facial recognition technology but instead identifies individual shoppers via their shape and movement pattern.

The team is based in San Francisco, California.

Why I like Them

This is technology that feels like the future. The main thing that consumers hate about brick & mortar shopping is the dreaded line at the cashier. Even more fascinating is the technology Standard Cognition has developed may be more advanced than Amazon’s own that powers their Go stores. They need significantly fewer cameras and hardware than an Amazon chain. The space is starting to get crowded however with several other startups and Microsoft developing their own offering.

Msg.ai

Overview

Msg.ai is an early stage startup that offers a SaaS machine learning product for companies to interact with their customers across all channels including SMS, social media, email, etc.  Basically they offer AI in a box targeting real time online customer service across social media and messaging channels.  When the conversation gets to complex for the AI, the system automatically hands it off to a human agent.  Their product works across a wide range of industries including CPG, eCommerce, online retail, etc.

Founded in October 2014, the company is based in San Francisco.  The founder, Puneet Mehta, is a former Wall Street IT leader and IBM engineer.

Why I like Them

Vertically focused specific use cases like this are where I think the interesting applications are of AI over the next 3-6 years.  Startups that find a way to use AI to automate specific human (aka expensive) processes such as digital customer service are interesting.  It's a relatively easy sell when you can show in a few months the savings dropping straight to a company's bottom line and management can reduce headcount in costs centers.

Even more interesting with Msg.ai is the access to their clients' unique proprietary datasets.  Years of one of a kind records of customer service exchanges in the past are datasets no one else in the industry has access to.  As I bring up time and time again on this blog,  with machine learning its less about the algorithms themselves and more about the proprietary data access they can train the models on that no one else can.

Msg.ai has had strong out of the gate success having already signed Sony and Heinz.  Sony reported in the first 3 months it was able to replace 70 human customer service staff due to Msg.ai technology while making their customer support responses faster.

Disclosure:  All information is from publicly available sources, I have not had any contact with a member of the company or its investors.

SoftWear Automation

Overview

SoftWear Automation is a startup in Atlanta founded by a Georgia Tech computer vision professor that is developing machine vision and robotics technologies for sewn apparel manufacturers.  Sewn apparel is still made by hand in emerging market countries because of the extreme difficulties in sewing cloth for machines.  Unlike with metals or plastics machine have difficulty in knowing where pieces of fabric are when trying to sew them due to their softness.  However, using SoftWear Automation’s machine vision software and systems manufacturing robots can now sew clothing like shirts and jeans more accurately and faster than humans.  The company has only raised $3M in funding to date. Pricing for a system ranges from $50k - $100k.

The company was founded by a computer vision expert at Georgia Tech named Steve Dickerson who currently acts as chairman. The current CEO is a serial entrepreneur named K.P. Reddy who has 20 years of technology entrepreneurship experience having started several IT and communications companies with successful exits.

The sewn apparel manufacturing industry is a $100B+ industry in the US alone.  In 2016 it is still nearly completely un-automated with the work done by humans with sewing machines.  For context, according to the International Federation of Robots in 2014, of the 230,000,000 industrial manufacturing robots sold globally, only 300 were for apparel manufacturing.  The challenge of machines sewing clothing is a technically hard problem hence why there are so little offerings in this space.

Why I like Them

I like them because their technology is head and shoulders  above what is currently on the market and they are already showing strong customer traction.

They started selling in October 2015 with customers making recurring orders especially among fast fashion and athletic apparel manufacturers. By all reports they have strong word of mouth with inbound calls daily from US and Asian apparel manufacturers interested in testing their products.  A strong proponent of their technology is American Apparel founder and serial apparel entrepreneur Dov Charney publicly stating he is using Softwear Automation’s technology in his new clothing venture.

By solving the extremely challenging technical problem of creating sewn apparel without the need for human hands, the product is an easy sell to garment makers. SoftWear Automation’s systems lower manufacturing costs, allow faster production times, shorter inventory cycles, removes liability from human labor, and allows greater customization of products (critical as apparel companies have been forced to have exponentially more SKUs in the last few years due to consumer demand).

Disclosure:  All information is from publicly available sources, I have not had any contact with a member of the company or its investors.