- Its technology leverages geospatial and business data as well as proprietary datasets to grow and optimize operations
- Businesses can ask questions, visualize current situations, and predict potential future scenarios
- Insights and recommendations developed via AI and machine learning displayed on an interactive map
DeepSpatial Inc is a software-as-a-service (SaaS) and artificial intelligence (AI) company that promises to answer every business question on the planet.
The Toronto-based company specializes in providing businesses with robust solutions powered by its AI and machine learning technology that leverages geospatial data along with business data as well as its proprietary datasets.
The company’s technology takes away the guesswork and risks behind making geospatial business decisions. It gives businesses the flexibility to ask questions, visualize current situations, and predict potential future scenarios. The result is increased productivity, lower costs, and improved profitability.
Here’s how it works: A company uploads its business data to the DeepSpatial AI platform. The data - like customer profiles, inventory management, and supply chains - are broken down into silos and displayed on live interactive maps, which the company calls geo-coding that allows for meaningful data analysis. Additional and far-reaching datasets, which include datasets proprietary to DeepSpatial, are uploaded onto the platform.
DeepSpatial’s AI engine learns from the business data by layering it with other data sets to identify the parameters that are vital to the business’ growth and profitability. These insights are displayed on the interactive map.
In turn, the client uses these location-based insights and recommendations to grow and optimize its business operations, such as pricing and right-sizing inventory to meet future market demand, identifying and exploiting the most advantageous supply chains to expand into high potential areas, and refining brand campaign messaging (ie. social media) to resonate with primary target audiences and to improve customer service offerings for its purchasing base. It can also help find new customers.
DeepSpatial is targeting brick and mortar retail chains such as grocers, pharmacies, and restaurants as well as building supply and consumer packaging goods firms. Governments are also on the list.
To date, DeepSpatial’s AI engine has been used successfully by several multinational clients that include some of the largest beverage firms, retailers, and governmental entities.
How is it doing:
In March 2021, DeepSpatial achieved a major milestone when it began trading on the Canadian Securities Exchange, giving it access to a wider investor base and boosting its capital fund-raising potential.
That same month, DeepSpatial introduced to shareholders and potential investors its new board of advisors composed of a diverse and experienced pool of talent with an impressive collective expertise to serve the company’s executive team through its continued growth and development.
Advisory board members include Sourav Sachin, VP of Engineering at BrowserStack and previously CEO of WoNoBo; Kapil Raval, director with Partner Ecosystem, Azure Global Engineering at Microsoft (NASDAQ:MSFT); Andrew Mandyam, founding partner of Utilis Consulting and previous director at Enbridge (TSX:ENB) Gas Distribution; Robert Luciano, CEO of DecisionSMART Retail Advisory, and previous director with Starbucks (NASDAQ:SBUX) Coffee Canada; and Pulkit Trivedi, director at Google (NASDAQ:GOOGL) and previous director with Facebook (NASDAQ:META).
Recently, the company announced two strategic hires - Debojyoti Purkayastha and Pramod Misra. They will help build operations by catalyzing growth across two central pillars of its core business, scaling business activity and enabling strategic data partnerships.
Purkayastha, who is now vice president for business development at DeepSpatial, was the regional director of India for Voyager Labs, an AI-powered analytics company based in New York. Misra, who now sits on the company's board of advisors, currently serves as the general manager and lead data scientist at Indian telecom company Vodafone (LON:VOD).
Meanwhile, DeepSpatial has taken several steps to expand its footprint in India as well as the overall South Asian market.
In February 2021, India liberalised geospatial data, allowing companies and individuals to conduct mapping and share geospatial data for various applications, including transport and e-commerce among others, without prior approval from the government. This presents a massive business opportunity for DeepSpatial, leading it to bring some heavy hitters on board.
The company recently recruited Kunal Singhal as its head of sales for India. He comes from Check Point Software Technologies (NASDAQ:CHKP) Ltd (a multibillion-dollar NASDAQ-listed software company) where he led sales in India.
DeepSpatial also recently signed a revenue-generating contract with DFM Foods, India, for a strategic geodemographic customer profiling and market expansion project. DFM Foods is a leading player in the snack foods market in India, and its flagship product – CRAX rings – is a household name in the second-most populous nation in the world.
The company will conduct a thorough analysis of product sales within different geographies to identify ideal customer archetypes and will use machine learning algorithms to identify predictable models for successful sales; employ geodemographic customer profiling to identify alternative markets for expansion in India, and target efficient delivery mechanisms and route optimizations strategies as well as create predictive models of demand and supply to better manage the production supply chain.
DFM will use the DeepSpatial platform for a flat fee and upon successful delivery, pricing will switch to an annual, SaaS-based pricing model.
More specifically, in highlighting how its technology works, DeepSpatial cited the example of a large retailer in India that sought out the company with a range of questions, such as how to bolster the success rate of new stores? Which are the best new locations? How can they increase sales and what parameters are critical (or not) to its success?
In turn, DeepSpatial identified new locations which led to a 45% increase in the success rate of new stores while scouting time for properties was reduced from 15 days to 3 days. The company was also able to predict the sales-per-square-feet within 90% accuracy of any location.
In North America, the coronavirus (COVID-19) pandemic has prompted an uptake of new disruptive technologies, as businesses that were traditionally focused on growing now are thinking of surviving, sustaining, maintaining revenue, and closing locations with less potential, among many other concerns. DeepSpatial has said it plans to target two heavily affected industries - retail and consumer packaged goods.
Inflection points:
- Penetrate deeper into India, South Asian, and North American markets
- Expand network of data partners and further develop proprietary datasets
- Uplist to OTCQB under ticker symbol DSAIF
“We are redefining how maps are perceived as our AI engine delivers real-time insights on a map and these are based on business data layered with our proprietary datasets," DeepSpatial CEO Dr. Rahul Kushwah has said.
"As such, for every client, the insights offered are unique to the client and to their business. Companies are sitting on piles of data and our technology to put it simplistically is taking that data and churning out insights that impact growth and profitability," he added.
Contact the author: patrick@proactiveinvestors.com
Follow him on Twitter (NYSE:TWTR) @PatrickMGraham