The retired ex-US-intel officer who started an AI business in Southeast Asia

Photo credit: Cyril Ng and SGInnovate

Photo credit: Cyril Ng and SGInnovate


Entrepreneurs are often eager to talk about their startups. Drew Perez, founder of artificial intelligence (AI) startup Adatos, seems like an exception to the rule. As I asked about Adatos, he seemed to steer clear of discussing it.

“Talking about the history of the company – that’s so myopic, right?” he says, preferring to discuss the big picture.

But it’s hard to ignore him and his company. Started three years ago, Adatos is one of the rare AI startups based in Singapore that focuses on agriculture.

Starting an AI company isn’t a typical retirement plan for most, but Perez isn’t typical. His goal is to find the right use case for artificial intelligence within Southeast Asia.

To do that, his team has automated the process of creating machine learning models – essentially an AI that builds its own AI to solve the problems specified by a human. The technology essentially takes on the role of a data analyst.

It was only in their third year that Adatos zoomed into its vertical of choice: agriculture. The startup acquires satellite imagery of farmland and processes them to produce data that can advise farmers on crop management.

Focusing on agriculture helps Adatos address a genuine need in the world — food security. With the world population rising, the Food and Agricultural Organization (FAO) estimate that the number of people undernourished in the world has been on the rise since 2014, reaching 815 million in 2016. With the population increasing, farmers are struggling to keep up.

Perez thinks data can help. Farmers can use satellite data to evaluate what land to buy, or how to manage their water and fertilizer better. They can help predict potential risks to crops, such as floods or soil fertility decline.

“If we can move the needle 0.0001 percent on getting more yield out of the land, it’s more than any of us could hope for in making an impact in the world, right? It’s a huge difference.”

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Adatos Chief Commercial Officer Jonathan Paul Talks AI for Precision Agriculture

Malaysia and Indonesia are responsible for almost 90% of the world's palm oil production. Chief Commercial Officer Jonathan Paul discusses why Adatos has decided to focus on the Precision Agriculture vertical at recent IBM conferences in Kuala Lumpur and Jakarta.

Jonathan Paul at an IBM Power9 Launch held in Kuala Lumpur on 15 May 2018.

Jonathan Paul at an IBM Power9 Launch held in Kuala Lumpur on 15 May 2018.

Ex-Group Head of Risk Markets for Standard Chartered Jonathan Paul joined Adatos formally as its Chief Commercial Officer in January 2018, after acting as a Senior Advisor to the company from June of 2017.

In a new phase of growth, Paul explained that the company will be focusing its efforts on the profitable agriculture industry, balancing game-changing A.I. technology capability with sustainable intensification principles. 

"The ready availability of geospatial data to train machines, Adatos' niche expertise in GEOINT (Geospatial Intelligence) and a highly profitable market makes this a sweet spot for the company to tackle," explains Paul. "The possibilities are endless, as we move even downstream to commodities pricing and trading."

Paul brings to Adatos over 25 years of experience at some of the largest financial institutions in the world.

Paul brings to Adatos over 25 years of experience at some of the largest financial institutions in the world.

Paul will be joining Managing Director Drew Perez in the leadership of Adatos, expanding its footprint across South East Asia and beyond.

"Adatos has the potential to be a huge business. I'm excited to get involved in the company's journey."

Meet the Adatos team here.

The Right Way To Put AI In Business

Many companies are in a hurry to cash in on the AI gold rush, but data-intelligence startup Adatos sets itself apart by only focusing on profitable use cases, says its Managing Director Mr Drew Perez. 


Interest in artificial intelligence (AI) is at fever pitch, prompting some venture capitalists to invest in AI companies that have little more than an idea, and large corporations to buy over AI startups that don’t even have a functional product.

“As transformative as AI undoubtedly is and will be, many people do not realise that not every problem needs to be answered with AI,” says Mr Drew Perez, Managing Director of Adatos, a company founded in 2015 to provide data intelligence solutions.

As psychologist Abraham Maslow once said: if you only have a hammer, there is a great temptation to treat everything as if it were a nail.

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The Peak’s inaugural “Great Minds at the Great Room” discussed ethical dilemmas of artificial intelligence

Artificial Intelligence experts Drew Perez and Violet Lim and venture capitalist Vinnie Lauria share their take on the pros and cons of using AI.


“For the first time in the history of humankind, we have machines doing brain, not brawn,” says Drew Perez, managing director of Adatos A.I., a Singapore-based artificial intelligence start-up. From virtual assistants such as Amazon’s Alexa to Netflix – which serves up films a viewer might enjoy based on his/her viewing history – applications of artificial intelligence technologies have become commonplace in our daily lives. And that’s set to grow. Research firm IDC predicts that the Asia-Pacific AI market alone will expand at a compound annual growth rate of 63.9 per cent between 2015 and 2020.

Perez was one of three panelists speaking at the inaugural edition of Great Minds at The Great Room, a talk series jointly presented by The Peak and co-working space The Great Room. The discussion titled “How to be a Futurist: Connecting the Dots of Current Trends” was moderated by Rosalind Tan, director of operations of Adatos A.I. and saw Perez joined by Vinnie Lauria, founding partner of venture capital firm Golden Gate Ventures, and Violet Lim, CEO and co-founder of dating company Viola.AI and Lunch Actually Group.

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Can Huawei untangle the AI mess?

Huawei is building a digital platform with “device-cloud synergy” to support artificial intelligence applications, but enterprises should be wary of being locked into a single AI stack

While enterprises already have a variety of AI-related offerings to choose from – including AI-optimised hardware from Lenovo, cloud-based AI services from Amazon Web Services (AWS), and software from niche players such as Adatos – they have to architect an entire technology stack to run their AI applications.

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AI: A Digital Swiss Army Knife

Like the multi-purpose pocket tool, artificial intelligence is adding value across diverse industries from healthcare to financial services.


In 2016, rats beset parts of Bishan, much to the chagrin of its residents, who encountered the unwelcome furry visitors in food centres, shopping malls and housing areas.

If you’ve never thought of pest control as a high-tech endeavour, think again. The authorities, not content to stick to traditional methods, roped in SmartCow, a Singapore startup specialising in industrial-grade artificial intelligence (AI) hardware, to help rid the area of the infestation.

To track the rodents’ movements, SmartCow attached thermal cameras to the undersides of drain covers in affected areas. It then used data analytics to automatically examine the collected images and determine the pests’ most-used underground routes.

“The pest controller was able to use the information to strategically place poison to kill the rats, saving manpower and resources,” recalls Ms Annabelle Kwok, SmartCow’s founder and CEO.

Like the Swiss Army knife, a clever gadget that can be used in all sorts of situations, the potential applications of AI across various sectors—including one as unexpected as pest management—is why startups and large enterprises alike are developing and adopting AI-based technologies.

Singapore is home to a burgeoning AI research and development scene. Recent figures from publishing giant Elsevier show that publications on the topic from Singapore are the second most highly cited in the world, behind Switzerland.

In addition, the Singapore government in May 2017 launched AI.SG, a S$150 million, five-year programme to fund projects that use AI to solve real-world problems, particularly those related to finance, healthcare and city management.

Automation gets an intelligence boost

Humans have for decades relied on machines to carry out routine grunt work. But with AI now enabling machines to handle more complicated tasks, this automation can be taken a step further. For instance, while most manufacturers still use manpower to monitor production lines for defects and errors, a few cameras coupled with data analytics software can do the job for a fraction of the cost, and with higher accuracy.

A large semiconductor firm in Singapore now uses another of SmartCow’s products—a portable device loaded with customised AI software that connects to cameras and sensors—to inspect its printed circuit boards.

“Our systems cost less than S$2,000 each, and can analyse images from cameras to detect whether any component is missing or placed in the wrong way, even if it’s just one millimetre to the left, rotated in the wrong direction or partially lifted from the board,” says Ms Kwok. “It can also generate reports on the percentage of components that are faulty, so that companies have that useful information when they are considering or negotiating with suppliers,” she adds.

Picking up the pace with autonomous robots

Although robots can now perform a wide range of activities, most still lack the ability to move around autonomously, says Mr Abhishek Gupta, co-founder and CEO of Singapore robot navigation startup Movel AI. Yet, autonomous robots would be tremendously useful, Mr Gupta points out. Logistics and construction firms, for example, could use automated ground vehicles and drones to transport goods and inspect work sites, reducing labour costs and improving safety. Self-navigating robots would also find many applications in homes, hospitals and other non-industrial settings, he says.

Stepping up its efforts in robot navigation, Movel AI is building advanced systems based on computer vision and software that can combine inputs from a number of different sensors, says Mr Gupta.

“Compared to the more common light detection and ranging (LIDAR) and radar navigation systems, ours is more lightweight and cost-effective, and provides robots with a better understanding of their surroundings,” he explains.

Several restaurants in Singapore are already using robots equipped with the company’s system to collect dirty dishes from dining tables, Mr Gupta shares. Movel AI is also discussing opportunities to deploy its technology with various other companies, including several that develop automated drones and vehicles, and a security corporation that wants to use robots for patrols, he adds.

Transforming the traditional

AI can also benefit industries where no heavy physical labour is involved—retailers, for example, can refine the way they stock their inventory.

“Traditional inventory systems can only tell retailers how many units of a product were sold. With deep learning models, we can identify customers’ characteristics, such as age and gender, to tailor promotions,” says Ms Kwok. “With computer vision, we can even measure the ‘bounce rate’ of physical items. If a particular handbag was picked up many times in the past two hours but not a single unit was sold, for example, that may signal to the retailer that its price needs to be lowered,” she adds.

Banks and financial services firms can improve their operations and bottom line through the use of AI programmes that better calculate the risks of providing financial services and products, says Mr Drew Perez, founder of Singapore-based start-up Adatos, which provides data intelligence solutions related to customer analysis, portfolio optimisation and data blending.

A large regional consumer bank in Southeast Asia used Adatos’s portfolio optimisation product to better assess the probability that retail customers would be late or default on loan payments.

“In the Asia Pacific region, there are markets where the majority of the population remains unbanked, and a national credit bureau is either not present or unable to provide accurate risk scores due to a lack of data from traditional sources,” adds Mr Perez.

Using data intelligence for risk analysis enables financial services firms to analyse non-traditional sources of data, such as mobile telephone credit ‘loads’, to get an accurate risk analysis before providing services to such previously untapped markets.

Despite the obvious potential of AI and robotics systems, obstacles to their widespread adoption remain. One of these is a lack of qualified data scientists, says Mr Perez.

“Talent in deep learning is scarce worldwide, and high demand for existing talent has inflated data scientists’ salaries to the point where only tech giants can afford them. Most qualified data scientists are immediately hired by the likes of Google and Baidu,” he explains.

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Artificial intelligence in various forms is not a panacea for every problem, but it can help enterprises fend off cyber attacks and get better at what they do.


Former US intelligence officer Drew Perez is an old hand at making sense of vast volumes of data using machine learning and artificial intelligence (AI) in the name of counter-terrorism and national security.


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