3. 03
Converge - Shaping AI for Southeast Asia
About
Converge
Converge is a series of reports by Deloitte Southeast Asia Innovation that provides
insights into the technology trends and startup ecosystem in Southeast Asia.
Each report provides a snapshot of the upcoming technology trends in a particular
sector and introduces promising startups that are driving new ideas and taking on
challenges that are unique to Southeast Asia.
Join us in discovering interesting and potentially disruptive startups and initiatives
across a myriad of industries and feel the pulse of Southeast Asia’s thriving digital
revolution!
Who the report is for:
• Corporations exploring innovation capabilities and startup engagement
• Individuals who are keen to understand technology and innovation trends driven
by the startup ecosystem in Southeast Asia
About Deloitte Southeast Asia Innovation
Deloitte Southeast Asia (SEA) Innovation is a cross-function, cross-country innovation
unit dedicated to driving the innovation agenda as a culture and value creator across
the region.
Have feedback on Converge? Drop us a note at
SEAinnovation@deloitte.com!
About Deloitte Cognitive Analytics Solution Centre of Excellence
Deloitte's Cognitive Analytics Solution Centre of Excellence (CASC) is a global initiative
supported by the Singapore Economic Development Board, that uses cognitive and
advanced analytics techniques to deliver risk sensing and predictions to global clients.
Limitations:
While we try our best to ensure that this report is up-to-date and accurate in the presentation of information as of the date of
publication, there are some limitations to this report. For example, some startups choose not to disclose their funding rounds
and/ or funding amounts. As such, the data might not reflect the exact situation.
Sources:
This report draws from startup databases such as Tracxn, Crunchbase, e27 and Tech in Asia; reported data from local, regional
and global news sources; as well as respective company websites.
4. Converge - Shaping AI for Southeast Asia
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The Era of Artifical Intelligence
Artificial intelligence (AI) is everywhere these days. Human beings
are building machines to perceive the world and make decisions
like human beings do, to the extent that machines may outstrip
the cognitive ability of the average person in the near future. As
machines become smarter, a whole array of concerns appear, from
the efficacy of the deployed AI to the ethics of letting machine-run
efficiency affect our jobs and our way of life.
The pinnacle of an AI future sits at the intersection of machine
learning brilliance and benefit to humans. In the business
context, a professional supported by a “super human” machine
can combine the best of what humans and machines have to
offer. That said, checks and balances will need to be built into the
human-machine interaction to safeguard against unintended
consequences.
The deployment of AI entails its own chain of activities, from
data collection and preparation to ‘train’ the AI, to investing
into component technologies that enable the promise of AI to
manifest. In the decades to come, startups, corporates and even
governments will continue to pursue machine learning excellence
in the many realms that AI will eventually enter, aided by the
continued improvements to supporting technologies such as
processing power and cellular network technology.
Explorations into frontier technologies – including deep learning,
industrial Internet of Things (IoT), image recognition, quantum
computing and 5G networks – will always be expensive. Big
technology companies like Google and Facebook, that have both
the financial means and an immense amount of customer data,
have a huge headstart on the AI race. That said, given the zeitgeist
of an open innovation ecosystem, smaller players have been able
to adopt some level of AI, which can still have long-lasting and
widespread impact on businesses and citizens alike.
In this report, we will explore the various ways Southeast Asian
startups have incorporated AI in their solutions to change the
way business is done in their respective countries. Often, this
is dependent on infrastructure provided by the big technology
companies. The startups then add a layer of contextual insights
and relevance in order for the AI to produce optimisation,
recommendation, and personalisation suggestions that suit their
market needs.
5. Converge - Shaping AI for Southeast Asia
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How to train your AI
Machine learning (ML) is a subset of AI that allows computers to
learn and improve on its own without intervention or programming
adjustments by humans. For an AI system to be effective, it is
very important for it to be fed with relevant data so that it learns
to recognise what it should and should not be processing. AI-
training is especially important when the tasks on hand deal
with unstructured data, like images and natural language, which
generally stray from pre-defined models and categorisations.
While enterprise-facing industry solutions like programmatic
advertising and cybersecurity are mostly able to run on the same
core technology regardless of location, public-facing industries like
retail and customer service require more customisation before
deployment, to be able to adequately manage the linguistic,
cultural and other differences that exist across countries.
Helping companies build AI that understands the local nuances
of this region are startups like Supahands and Next Billion (see
Table 1), which have emerged to provide or collect data points as
required by clients. Relying on the gig economy, these startups are
able to amass huge localised datasets efficiently through mobilising
a crowdsourced workforce armed with affordable camera
smartphones. With such data points, they are able to provide
businesses with contextually-accurate insights.
Recognising Diversity
When Apple released the Face ID feature with the
iPhone X in 2017, the idea of using facial recognition as a
biometric security layer gained mainstream interest.
However, it also brought up the problem of AI being
trained on a skewed dataset. A lady from China claimed
that the iPhone X could be unlocked by her colleague
with Face ID. This occurred even after getting the initial
unit exchanged, prompting discussion about whether
the AI software itself was the problem as opposed to the
hardware1
.
Other companies like Google, Hewlett Packard and Nikon
have also experienced embarrassment previously, when
users shared online about instances in which their facial
recognition software failed to recognise non-white faces
in particular.
Giving AI a Southeast Asian flavour
Table 1 - Startups digitalising data collection
Startup Description Country Founding Year Total Funding
Supahands
http://www.supahands.com
Supahands provides training data for
ML and AI, collected using proprietary
technology and a crowdsourced
workforce.
Malaysia 2014
Series A -
Undisclosed
Next Billion
https://www.nextbillion.asia
Next Billion builds data platforms to
provide insights into communities,
consumers and retail trends.
Singapore 2013 Undisclosed
*Information and numbers sourced from Crunchbase, Tracxn and company websites
1. https://www.newsweek.com/iphone-x-racist-apple-refunds-device-cant-tell-chinese-people-apart-woman-751263
6. Converge - Shaping AI for Southeast Asia
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Can bots speak my language?
A low-hanging fruit for any customer-facing business looking to improve their operations with AI is the implementation of a chatbot, which
makes for a cost-effective service agent that can work 24/7 when properly trained. One of the biggest challenges for chatbot adoption in
Southeast Asia, however, is the lack of Natural Language Processing (NLP) ability.
Southeast Asia is home to a myriad of languages, dialects and vernacular, and effective NLP ability for this region needs to process
everything from Thai to Teochew (a Chinese dialect), to the distinctions between Manglish (Malaysian English) and Chinglish (Chinese
English). Indonesia alone speaks over 700 languages and variants2
.
The lack of suitable NLP libraries to train AI in local languages has been noticed, and startups in the region have endeavoured to fill this
gap by creating chatbot companies and building up NLP libraries (see Table 2). Beyond improving the linguistic ability of bots, these
startups are also catering to their local markets by developing chatbot solutions on social media and communication platforms that have
the highest adoption locally, and are embedding their solutions on platforms like Whatsapp, LINE, and Facebook Messenger instead of the
usual websites. In addition, startups like Kata.ai and BJTech also provide developer suites, allowing local businesses to use their technology
to build their own solutions, enabling more end-users to benefit from the ease of accessibility and instant responses that chatbots can
provide.
When bots learn to be too human
In 2016, Microsoft created a Twitter bot named Tay that learnt
to speak casually from interacting with users on Twitter.
Microsoft had to shut it down within a day because it quickly
devolved into a racist, sexist and hate-spewing internet troll3
.
After the disastrous social AI chatbot experiment with
Tay, Microsoft released a politically-correct version of Tay.
Called Zo, it has the persona of a stereotypical teenage girl,
who gives a wide berth to politics and any other potentially
inflammatory topics4
.
Machines mimicking human communication perfectly may
be a worthy technical aspiration, but it may not always be a
desirable one, if it is a facet of humanity that should not be
bestowed with super-human capabilities.
2. https://www.techinasia.com/indonesia-foreign-startups-10-things-know-list
3. https://gizmodo.com/here-are-the-microsoft-twitter-bot-s-craziest-racist-ra-1766820160
4. https://qz.com/1340990/microsofts-politically-correct-chat-bot-is-even-worse-than-its-racist-one/
Table 2 – AI chatbot startups
Startup Description Country Founding Year Total Funding
Kata.ai
https://kata.ai
Conversational AI company, providing
the ultimate toolset for developers to
build sophisticated chatbots.
Indonesia 2015
Series A -
US$3.5M
BJTech
https://bjtech.io
AI conversation platform designed for
small and medium businesses that
want to enhance their customer care
experience.
Indonesia 2015 Seed - US$1.2M
Zwiz.AI
https://www.zwiz.ai
AI chatbot and analytics platform for
business.
Thailand 2017 Undisclosed
Expa.AI
https://expa.ai
A unified solution for sales, marketing
and customer support.
Myanmar 2017 Undisclosed
Source: Crunchbase, Tracxn, respective company websites.
7. Converge - Shaping AI for Southeast Asia
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From digitalising field operations…
While the push for digitalisation is not new, the growing promise of AI to bring about deeper insights and greater productivity is giving new
impetus for businesses to transform their manual recording and field operations.
Traditionally, roadshow promoters and retail auditors have been offline channels for collecting marketing insights. Increasingly, these roles
are becoming the bridge between the offline and online worlds — field personnel are now able to digitally collect text and images easily,
neatly and immediately from their on-the-ground interactions, when equipped with a customised phone or tablet application. Effectively,
offsite employees can now feed real-time information into an online database, which the wider business can then act on more quickly as
well (see Table 3).
...To achieving cost savings with smarter automation and hardware
Business automation, which can relieve the human workforce from repetitive standardised tasks, is an aspect of business improvement
that is getting a boost from the development of AI as well.
Highly improved photographic, telephonic and sensing technology is allowing vast amounts of good quality information to be captured
from scanning anything, from documents to calls in the work environment. In tandem with this development, the ability of AI to
understand and process unstructured data is expanding the scope of processes that can feasibly be automated. AI-powered process
automation is able to help businesses keep a constant watchful eye on systems, observing data and workflows in real-time, and acting on
known issues that match identified patterns.
TAIGER is a Singapore-based startup that specialises in providing intelligent process automation. This can take the form of user-facing
interfaces like chatbots and virtual assistants to handle clients and help staff, or systems running in the background that automatically
recognises, extracts and processes information from uploaded data. TAIGER claims that its AI has been able to help its banking, insurance
and government clients slash processing time by up to 90% and reduce costs by up to 80%, while maintaining about 90% accuracy5
(see
Table 4).
In June 2019, TAIGER signed a global strategic alliance with image and photographic scanning equipment manufacturer Kodak Alaris. By
combining TAIGER’s AI software with Kodak Alaris’ hardware, document scanners are transformed into intelligent productivity tools, with
superior Optical Character Recognition (OCR) that can immediately capture scanned information for automated processing6
.
5. https://ie.enterprisesg.gov.sg/media-centre/news/2018/3/ai-firm-taiger-gives-clients-more-bite-in-slashing-costs
6. https://www.alarisworld.com/en-gb/about-us/newsroom/2019/taiger-kodak-alaris-strategic-alliance
Source: Crunchbase, Tracxn, respective company websites.
The AI Augmented Worker
Table 3 – Field operations productivity startups
Startup Description Country Founding Year Total Funding
Powata
http://powata.com
Powata offers technology solutions
for retail workforce management.
Singapore 2017 Undisclosed
BetterTradeOff
https://bettertradeoff.com
BetterTradeOff reinvents financial life
planning with big data and analytics.
Singapore 2015 Seed - SGD$3.4M
Eko
https://www.ekoapp.com
Eko is an internal communication and
operations platform for businesses
to bring together the right people,
information, and tools to get work
done.
Thailand 2012
Series B –
US$28.7M
8. Converge - Shaping AI for Southeast Asia
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As intelligent business process improvements continue to garner interest, startups are also finding niches to serve. Singapore-based
Exact.ai, for instance, aims to transform back office operations for the media and advertising industry by providing sector-appropriate
tools for payment and reconciliation, compliance control and auditing, and delivery tracking.
From monitoring to processing to optimising workstreams, the role of the human being in such functions will definitely be affected as
smart machines take up more of the load.
Source: Crunchbase, Tracxn, respective company websites.
Table 4 – Workforce and process automation startups
Startup Description Country Founding Year Total Funding
TAIGER
http://taiger.com
TAIGER provides robotic process
automation solutions primarily
serving the banking, insurance, and
government sectors
Singapore 2009
Series B -
US$31.3M
Exact.ai
https://www.exactai.com
Exact A.I. is an automated delivery
reconciliation and payment platform
for media. Using proprietary A.I.,
they support and improve back and
middle office processes.
Singapore 2018 Undisclosed
Will AI kill jobs?
This perennial question will never grow old. From automation to AI, technological progress has always caused human beings to
worry about being displaced by robots.
A September 2018 report released by Cisco and economic consultancy Oxford Economics7
postulated that by 2028, 6.6 million
jobs will be lost across the six largest economies within the Association of Southeast Asian Nations (ASEAN) grouping due to the
adoption of AI and technology. Referring to Singapore, Malaysia, Thailand, Indonesia, the Philippines, and Vietnam, the research
found that the biggest job losses based on the “displacement effect” would be in the agriculture & mining sector (see Fig.1). On
the other hand, many other sectors are expected to see a net gain in job creation due to the “income effect”, or the productivity
growth from deploying smarter machines.
If history has taught us anything, jobs will ultimately continue to exist, but the new jobs created from technological advancement
will require a new set of skills. Those who fail to transition will need the social support of the state and other welfare providers to
find their footing in this new economic order.
7. https://www.cisco.com/c/dam/global/en_sg/assets/csr/pdf/technology-and-the-future-of-asean-jobs.pdf
4.3-10.1
4.9
2.9
6.1
3.9
1.9
3.9
0.2
- 4.3
-2.0
- 4.4
- 2.9
- 1.2
- 3.0
% Change
5.5%
11.7%
11.5%
13.5%
11.5%
13.4%
13.6%
10.7%
% Change
- 12.9%
- 10.3%
- 9.2%
- 9.4%
- 8.2%
- 10.0%
- 8.4%
- 8.4%
Agriculture & Mining
Manufacturing
Utilities
Construction
Wholesale & Retail
Transport & Tourism
Business Services
Goverment &
Community Services
- 0.1
Fig.1. Positive and negative impact of increased tehcnology adoption, by industry sector
(ASEAN - 6, number of workers (axis), percentage of workforce (labels), 2018 - 2028)
Millions of full-time equivalent (FTE) workers
Source: Oxford Economics, Cisco
9. Converge - Shaping AI for Southeast Asia
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The AI Augmented Industry
Behavourial patterns: a personalisation opportunity for businesses
With improvements to hardware and IoT sensors, data collected is getting increasingly personal. From individual preferences based on
tracked frequency and intensity of usage, to one’s gait and mannerisms, so much can be uncovered about the uniqueness of a person
from triangulating a few data points.
With AI becoming more powerful and accurate over time, mass personalisation is no longer an oxymoron. While the implications may be
more ominous for individuals, this development of AI enables businesses to take a look at individual customer profiles, such that they can
better provide individualised services and offerings, and also pick up on specific risk profiles.
As employee and customer transactions move online onto the increasingly intelligent smartphone, the opportunities for AI to promote
topline growth and manage risks are available to almost every industry.
10. Converge - Shaping AI for Southeast Asia
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1. Security and identify verification
While two-factor authentication remains a norm, new technology
is enabling other forms of biometric identification to become more
effective as security layers.
Helping e-commerce players block fraudulent transactions is
Singapore-based startup CashShield. Boasting real-time fraudulent
pattern recognition even for new users without much historical
data, coupled with passive behavioural biometrics, CashShield
claims to apply principles of high frequency trading to make instant
decisions on whether or not to block transactions (see Table 5).
Meanwhile, AI is also allowing voice to become a biometric
identifier. China-based VoiceAI has patented solutions providing
identity verification through the signal processing of a mere two
or three seconds of user speech. Language-agnostic and relying
instead on diction and other physiological indicators that can be
assessed through speech, this technology has been deployed to
facilitate the disbursement of pension funds for about 2.5 million
retired civil servants in Indonesia.
.
Source: Crunchbase, Tracxn, respective company websites.
Table 5 – Identity verification startups
Startup Description Country Founding Year Total Funding
CashShield
http://cashshield.com
CashShield helps companies manage
their risks from fraudulent payments
and hostile accounts.
Singapore 2008
Series B -
US$25.5M
VoiceAI
http://www.voiceaitech.com
VoiceAI is the industry's leading
provider of voiceprint recognition and
intelligent voice solutions.
China 2016 Seed - CN¥10M
11. Converge - Shaping AI for Southeast Asia
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2. Personal recommendation and consultation
From media content streaming platforms like Spotify and Youtube,
to e-commerce platforms like Lazada, it is common for media and
consumer platform applications to provide recommendations that
keep users engaged with the repeated use of the platform. In order
to generate these suggestions, these businesses track consumer
use and preferences on both an individual level and aggregated
user segments, sliced and diced from the overall dataset in various
ways. Understanding the propensities of individual choices vis-à-
vis other user profiles and segments allows businesses to better
tailor their communication efforts and content for each user, which
boosts engagement and sales.
In the healthcare sector, personalising data-driven predictions and
recommendations has more serious implications for one’s well-
being.
Healint, a Singapore startup, is the developer of a migraine tracking
software called Migraine Buddy which helps individuals keep track
of their migraine patterns and pre-empt migraine attacks (see
Table 6). Using the combined data of over a million registered
users from all over the world, Healint generates real world evidence
for patients, doctors, and researchers to understand migraines
better and work towards improving treatment outcomes8
. With the
data from Migraine Buddy, Healint has worked with pharmaceutical
giant Novartis on several research pieces on migraines.
Is AI better than the doctor?
Did you know that bone fractures are most likely to be
misdiagnosed between 8pm and 2am? A misdiagnosis
prolongs pain and injury as patients and doctors do not
pursue the necessary treatment.
Working on this problem is LogixLab from Malaysia
(see Table 6), which has developed an AI-powered
diagnostic imaging analytics solution. Aimed to help
physicians rely less on their naked eye to pick out a single
hairline fracture, the AI solution would deliver X-ray
descriptions, identify specific lesions of interest, and
suggest treatment. It would be able to do so consistently,
regardless of the time of the day.
8. https://www.businesswire.com/news/home/20180819005021/en/Healint-Announces-
Research-Showing-Increase-Anxiety-Depression
Source: Crunchbase, Tracxn, respective company websites.
Table 6 – AI-powered healthcare startups
Startup Description Country Founding Year Total Funding
Healint
https://www.healint.com
Healint is the developer of the
migraine tracking and research
platform, Migraine Buddy.
Singapore 2013
Series Unknown -
US$1.4M
LogixLab
https://www.logixlab.tech
LogixLab aims to provide advanced
and accurate AI-powered software
for imaging analytics.
Malaysia 2017 Unknown
8. https://www.businesswire.com/news/home/20180819005021/en/Healint-Announces-Research-Showing-Increase-Anxiety-Depression
12. Converge - Shaping AI for Southeast Asia
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AI is also starting to help shed light on areas that have been more
of an art than a science, one example being human resource
management. Removing most of the guesswork, IBM announced
early in 2019 that their AI can predict with 95% accuracy when
employees are about to quit, allowing HR to plan for early
intervention and coaching to avoid unnecessary attrition9
.
For jobs that require personnel to work with hardware and other
physical resources and facilities, it is also possible for AI to tie
the various elements together into a single dashboard view for
continuous monitoring, complete with prompts and alerts based
on AI-powered analysis.
By implementing various monitoring infrastructure - including
wearables, telematics and computer vision - industries as wide-
ranging as manufacturing, farming, trucking, facilities management,
and construction can all be analysed in real-time and monitored
for predictive maintenance and intervention. Now that planners
have a better understanding of the status of every single element
in motion, as well as environmental factors that may affect
the output, businesses are able to deploy software, hardware,
materials and human resources more optimally (see Table 7).
9. https://www.cnbc.com/2019/04/03/ibm-ai-can-predict-with-95-percent-accuracy-which-
employees-will-quit.html
Looking at team sports through AI
Team sports can be said to be a microcosm of what happens
at the workplace, condensed into an intense session of
competition, in which individual talents have to work well
together as a team in order to win.
In the world of e-sports, research organisation OpenAI
built an AI that defeated a team of professionals and world
champions at Dota 2, which is an immensely complicated
multi-player team game with a huge number of characters
and other game elements10
.
The permutations for Dota 2 are endless, and many situations
are happening at any given moment in the match. For OpenAI
to be able to train its AI to win Dota 2 shows that current
AI technology and machine learning techniques are able to
tackle large-scale and complicated scenarios, upping the ante
on the type of mainstream problems AI will be able to solve in
the years to come.
10. https://www.theverge.com/2019/4/13/18309459/openai-five-dota-2-finals-ai-bot-
competition-og-e-sports-the-international-champion
3. Resource management and monitoring
9. https://www.cnbc.com/2019/04/03/ibm-ai-can-predict-with-95-percent-accuracy-which-employees-will-quit.html
10. https://www.theverge.com/2019/4/13/18309459/openai-five-dota-2-finals-ai-bot-competition-og-e-sports-the-international-champion
13. Converge - Shaping AI for Southeast Asia
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Source: Crunchbase, Tracxn, respective company websites.
Table 7 – Resource management and monitoring startups
Startup Description Country Founding Year Total Funding
Lauretta.io
https://www.lauretta.io
Lauretta.io leverages on AI, ML and
big data to provide human resource
management solutions.
Singapore 2016 Undisclosed
SmartAHC
https://www.smartahc.com
SmartAHC provides IoT-based data
collection and analytics solutions for
pig farming.
China 2015
Series A -
US$2.9M
DRVR
https://www.drvr.co
DRVR provides fleet management
and analytics.
Thailand 2014 Seed - US$522K
Striking the balance
Effective AI for businesses can only result from the concerted
effort of those across the entire value chain, with a balanced
consideration for both technological excellence and the humans
interacting with the technology. The progress of AI is also
dependent on the state of complementary technology to track and
sense elements that may otherwise be imperceptible to the regular
person.
The open innovation ecosystem remains an important bedrock for
the development of AI and all its use cases, and new possibilities
emerge when new data inputs are available. As AI practitioners
seek new streams of highly localised data to aggregate, analyse
and act upon, however, valid concerns about data privacy and
information sharing will naturally continue to be raised. Already,
such concerns have led to the emergence of standards like the
General Data Protection Regulation (GDPR) in the European Union.
It will be necessary to find the right balance between safeguarding
privacy and promoting innovation as the AI industry continues to
develop and grow.
While this report is focused on the enterprise uses of AI, AI
can already be seen in many aspects of our day-to-day lives.
The growing incorporation of AI into enterprise solutions only
means that we will come to interact with it more and more, as an
employee, a customer and a resident.
The interaction between humans and technological advancement
will continue to enthrall and worry us all, but one thing is for sure:
even as AI becomes more integrated into the workplace, the need
for human labour will remain, although the concept of work and
competitive advantage will change. It will be important for societies
to adapt to AI augmented demands on a workforce and take care
of those who may get left behind, in order for the promise of AI to
prevail for the greater benefit of humanity.
