From Honey Bees to Heavenly Bodies and Account Receivables –Business Problems AI is Solving
Use cases for AI are as varied as every device and every human who generates a data point. Here are four examples of AI companies solving real world problems that demonstrate the variety of opportunities available to entrepreneurs and the scale of those opportunities.
1. Enhancing customer experiences in the metaverse
The future of customer experience in digital worlds will be key to winning in all the places people do business, work and play. That’s the premise that led to the creation of Soul Machines.
Founded by New Zealanders Greg Cross, a serial tech entrepreneur (who inter alia built and sold the tech that Apple uses for wireless charging) and Academy Award winner Mark Sagar in 2016, Soul Machines pioneered the creation of autonomously animated digital people in the metaverse and the emerging digital worlds of today.
The company recently announced its US$70 million Series B1 financing led by new investor SoftBank Vision Fund 2.
Together, the founders have created a solution that delivers life-like Digital People using their Human OS Platform and patented Digital Brain™ technology.
Their AI-powered, 3D Digital People can move their bodies, gesture, be aware of, and interact with on-screen content allowing brands to enhance customer engagement. The goal is to enable their customers to deliver highly personalized, engaging, and empathetic experiences, all in real-time.
Additionally, the company recently signed a five-year partnership agreement with Microsoft, in which the companies will collaborate on new products that will take AI applications to a new level and direction, ultimately transforming the way we interact with computers.
Soul Machines says it is dedicated to enhancing the future of meaningful customer experiences through highly personalized brand engagement – at scale. Simultaneously, Soul Machines can collect valuable customer insights in a way that has not been possible before.
The company has secured partnerships with global brands and celebrities including Carmelo Anthony, NESTLÉ® TOLL HOUSE®, Twitch, The World Health Organization, The Pan American Health Organization, Healthy Soil Biomes, and more.
Why AI? Soul Machines’ Digital People are supplied with the interactive, AI-powered face and voice that registers emotional cues from the customer and modulates voice and expression in response.
This helps customers feel much more comfortable interacting with an AI-powered customer service system. AI enables brands to curate a digital workforce that represents their brand identity, engages customers empathetically and ultimately drives brand loyalty.
2. From honey bees to satellites
Australian AI software company Xailient works exclusively in the field of computer vision and has developed a solution to a major problem facing companies using IoT: needing to send data back to the cloud to be processed. Latency issues are unacceptable where real time results are critical, and shunting data back and forth drives up energy and compute costs.
While co-founder Shivy Yohanandan was working on his PhD at MIT, he realised that existing AI solutions for computer vision were basically utilising brute strength to solve problems like facial recognition. That meant taking every data point available, loading it into the cloud, and trying to process it all.
Yohanandan realised that the human brain takes a smarter path, and only selectively absorbs the data it needs. This revelation led to the foundation of the company.
According to Mark Crosling, Xailient’s Director of Marketing, “We only concentrate on what’s of interest and cut out all the rest of it. Imagine a person walking down the street. Well, you can get rid of the cars and the buses and the trees and everything. Just concentrate on that person. That’s detection, and detection is the hardest part in computer vision.”
That ability to isolate selectively is incredibly powerful, and can be applied to myriad business problems. One example is the Purple Hive project being run in conjunction with Australian food company Bega.
Xailient’s AI software is used to identify Varroa destructor mites which attach themselves to bees to gain access to a hive, resulting in a potentially significant loss for the primary producers.
Another Australian business, Vimana Tech, combined the worlds of AI and IoT in the Purpose Hive project. It is responsible for the design and development of the physical hardware and IoT devices that connect to the Purple Hive to run the software and algorithms.
According to Vimana’s Joel Kuperholz, “AI in the context of computer vision allows for humanly impossible monitoring 24/7 with consistent accuracy – no sick days or human error.”
Worlds away from the Bega project, Xailient is also working with US analytics giant Palantir, whose Meta Constellation software integrates satellites from multiple providers to enhance coverage. To do this, those satellites need to retask to different analyses based on what they see. Xailient says it enables this through onboard analysis, eliminating the need for a downlink to the ground station.
While the Bega and Palantir projects may seem entirely removed from each other, they share one very important trait: they need to process data at the edge, and Xailient excels at edge computing.
3. Augmenting industrial expertise
Indian AI startup ExactSpace is an early-stage company focused on applying AI in the industrial sector – particularly in the area of sustainability, where it believes its AI solutions can help businesses decarbonise their industrial plants.
The company, founded by Rahul Raghunathan, Arun Jose and Boben Anto in 2018, is looking to blend machine learning and artificial intelligence with deep domain expertise in Pulse – its industrial AI framework.
While it’s early days, its solutions are already deployed in over 60 plants around the world, and the founders believe they are chasing a $100 billion market opportunity.
Unlike many AI-based automation platforms, which seek to supplant human decision-making – particularly around repetitive and low-value matters – Pulse is designed to augment decision-making.
As an example, ExactSpace says it has collected the expertise of over a hundred subject matter experts to help design its solutions for thermal power plants in areas such as fleet monitoring, performance optimization and predictive maintenance.
Ultimately, its goal is to build vertical-specific solutions across a range of industries in addition to thermal power – including refineries and chemicals, metals and manufacturing.
In late February the company revealed it had secured seed funding from a consortium led by Thermax Limited – an Indian engineering business specializing in energy.
At the time of the announcement, Thermax CEO Ashish Bhandari said, “Our investment in ExactSpace is a step to augment our digital capabilities.”
4. Taming documents
Singapore-based Docsumo is an early-stage document AI business developing solutions to convert unstructured documents into actionable data. It recently raised around $3.5 million in seed funding from Arbor Realty Fund.
Its solution is designed to help companies make faster and more accurate decisions, by capturing and analyzing unstructured data from documents such as tax returns, financial statements and invoices.
According to Docsumo co-founder Rushabh Sheth, “Document understanding is difficult – unintelligent and template-based Optical Character Recognition (OCR) solutions just don’t cut it. My co-founder Bikram used to be a data entry agent in Nepal to earn side income and knew how tedious and boring data entry is. However, the problem is a lot more complicated to automate since we as humans can make sense out of unstructured images, whereas machines need structured data for decisions.”
Docsumo’s solution, which it calls Intelligent Document Processing (IDP) is more than just OCR. It employs AI-based algorithms to recognize data types and build taxonomies to impose structure on data in a way that computers can use. It can even extract text from images.
Applications range from the obvious efficiencies for banking and financial services companies to insurance assessment, logistics and healthcare. Anywhere masses of data need to be extracted from paper and injected into analytical systems, the company’s founders see an application.