Earlier in January this year, TAIGER was featured in Nikkei Asia’s Business Spotlight for our ability to decipher complex documents using a hybrid AI approach setting us apart from tech giants like Google and IBM.
TAIGER coined a “Soonicorn”.
One successful case was streamlining Banco Santander’s customer onboarding process from several days to just 15 minutes. A correspondence from Santander told Nikkei Asia that they tested AI products from some of the tech giants but none produced results as accurate as TAIGER which delivered over 90% accuracy. Another testament to the effectiveness of TAIGER’s hybrid AI approach was when it was chosen to replace IBM’s Watson AI engine for a large Spanish paralegal service provider.
These examples have placed TAIGER in the category of a “soonicorn” as covered by DealStreetAsia. TAIGER is turning heads and especially in the Southeast Asia region, it might just come up on top as a leader in the emerging field of hybrid AI technologies.
The downside to machine learning.
Our founder and CEO Sinuhe Arroyo believes that existing solutions offered by tech giants often fail to meet the needs of customers due to its overdependence on machine learning which is but one discipline of AI. Machine learning has its weakness in that it requires huge amounts of data to find meaningful patterns. This isn’t practical for businesses as it becomes time consuming and labour intensive. Moreover, even if such massive amounts of data were available and fed to the machine, it often fails to “understand” the meaning of what it is analysing because it lacks basic knowledge. This is why TAIGER’s symbolic AI approach focuses on building a knowledge map of rules (ontology) determined by humans first before leveraging natural language processing to understand what the machine is looking at. This is the opposite of machine learning which first looks at the data before determining patterns and relationships.
Hybrid AI approach is gaining popularity.
In fact, this hybrid approach has been on the rise and even MIT-IBM Watson AI Lab is advocating this approach with its new technology platform dubbed “neurosymbolic AI”. Senior director analyst at Gartner, Anthony Mullen also highlighted that “the hybrid AI approach is the more complete approach to natural language automation”. Gartner had listed TAIGER as a vendor in its Hype Cycle report in 2020.
Nikkei Asia spotlights TAIGER’s hybrid AI approach that proves more effective
Earlier in January this year, TAIGER was featured in Nikkei Asia’s Business Spotlight for our ability to decipher complex documents using a hybrid AI approach setting us apart from tech giants like Google and IBM.
TAIGER coined a “Soonicorn”.
One successful case was streamlining Banco Santander’s customer onboarding process from several days to just 15 minutes. A correspondence from Santander told Nikkei Asia that they tested AI products from some of the tech giants but none produced results as accurate as TAIGER which delivered over 90% accuracy. Another testament to the effectiveness of TAIGER’s hybrid AI approach was when it was chosen to replace IBM’s Watson AI engine for a large Spanish paralegal service provider.
These examples have placed TAIGER in the category of a “soonicorn” as covered by DealStreetAsia. TAIGER is turning heads and especially in the Southeast Asia region, it might just come up on top as a leader in the emerging field of hybrid AI technologies.
The downside to machine learning.
Our founder and CEO Sinuhe Arroyo believes that existing solutions offered by tech giants often fail to meet the needs of customers due to its overdependence on machine learning which is but one discipline of AI. Machine learning has its weakness in that it requires huge amounts of data to find meaningful patterns. This isn’t practical for businesses as it becomes time consuming and labour intensive. Moreover, even if such massive amounts of data were available and fed to the machine, it often fails to “understand” the meaning of what it is analysing because it lacks basic knowledge. This is why TAIGER’s symbolic AI approach focuses on building a knowledge map of rules (ontology) determined by humans first before leveraging natural language processing to understand what the machine is looking at. This is the opposite of machine learning which first looks at the data before determining patterns and relationships.
Hybrid AI approach is gaining popularity.
In fact, this hybrid approach has been on the rise and even MIT-IBM Watson AI Lab is advocating this approach with its new technology platform dubbed “neurosymbolic AI”. Senior director analyst at Gartner, Anthony Mullen also highlighted that “the hybrid AI approach is the more complete approach to natural language automation”. Gartner had listed TAIGER as a vendor in its Hype Cycle report in 2020.
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