The Nvidia accelerator provides Algo.ai with resources as it continues to develop deep learning architecture and adds machine learning and augmented reality features to its platform.
Algo.ai’s updated Algo 2.0 platform launched in late 2017. It processes big data along the supply chain for products on the shelf at retailers such as Target Corporation TGT, Walmart Inc WMT and Best Buy Co Inc BBY.
“The collaboration supports our expansion of Algo into AR applications, ensuring our platform continues to be on the cutting edge and cementing our place as a market leader in our chosen verticals,” Algo.ai CEO Amjad Hussain said in the announcement of the Nvidia partnership.
Algo.ai was previously known as Algomus before a recent rebranding. The company made just under $5 million in 2017 and expects to end 2018 at twice that revenue figure.
While Algo.ai will likely seek growth capital in the future, in the form of $10 to $20 million in venture capital or private equity, Hussain said his company is self-sustaining.
“Right now we are able to grow revenue and invest all of that back into R&D.”
‘A Huge Business Case’ For AR
In a corner of Algo.ai’s suburban Detroit office, its position at the forefront of augmented reality development is on display.
The faces of celebrities like Katy Perry and Kim Kardashian flash on a tablet before their makeup is applied to the face of the user in real time.
The Algoface platform is in use with early adopter customers and in beta testing.
Cosmetics applications — such as the ability to see how a Kardashian’s makeup looks on one’s face — are only one use of Algo.ai’s facial recognition technology, Hussain said.
“It has a huge business case behind it. You have empowered customers to try different products.”
Algo.ai CEO Amjad Hussain describes the Algo 2.0 platform’s workflow in the company’s Troy, Michigan offices. Photo by Dustin Blitchok.
The company developed facial recognition software that compares 16 text descriptors of faces that were recommended by makeup artists to create a profile that can be compared against a photo database, said Taleb Alashkar, a computer vision scientist at Algo.ai. Algoface then assigns a probability to whether the description and photo are a match.
Hussain said few companies are developing technology of this kind, “and when they do, it’s snapped up by beauty brands.” He describes Algoface as one of the “Lego blocks” underpinning the Algo platform.
“It’s a very hot area, and this sort of technology is not available.”
European Expansion Next For Startup
When Benzinga first interviewed Hussain one year ago, the company’s average client was interacting with the Algo platform on 100 to 200 tasks or questions per day.
The number has since risen to 1,000 to 2,000 times a day as Algo handles processes such as shipments, inventory, points of sale, returns and planograms.
A 3.0 version of the Algo platform is being readied for a late 2018 launch. The technology is becoming more automated, Hussain said.
“Algo is going to proactively set its own tone and agenda and start asking questions itself and doing the work itself.”
A new product introduction is a good example of how Algo 2.0 and human collaborators work in concert — and a process that will never be fully automated, the CEO said.
“That’s the beauty. It’s not just AI or people. Together, you arrive at a better outcome.”
The company is expanding in Europe next, to the supply chains for such retail giants as Tesco, Hussain said, and Algo.ai’s existing customers are to thank for the new business.
The startup reports zero customer churn since its launch, he said.
“It’s our customers spreading the good word.”