T
Awaira Score
45
Out of 100
Valuation
N/A
Post-money
Total Raised
$20M
All rounds
Awaira Score
45/100
Founded
2014
100-500 employees
What They Build
March 2026Tookitaki builds AI anti-money laundering and financial crime compliance technology for banks and financial institutions, providing the Anti-Money Laundering Suite that uses machine learning to improve transaction monitoring accuracy, reduce false positive alert rates, and enhance suspicious activity detection across financial transaction data. The Singapore company also operates the Typology Repo…
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StageSeries B
Employees100-500
Country🇸🇬 Singapore
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Funding Rounds
Series B · No public funding round data available yet.
Founded Same Year (2014)
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View all alternatives to Tookitaki →Frequently Asked Questions
What is Tookitaki's valuation?▾
Tookitaki's valuation is not publicly disclosed.
Who invested in Tookitaki?▾
Investor information for Tookitaki is not publicly available at this time.
When did Tookitaki last raise funding?▾
No public funding round data is currently available for Tookitaki.
How many employees does Tookitaki have?▾
Tookitaki has approximately 100-500 employees.
What does Tookitaki do?▾
Tookitaki builds AI anti-money laundering and financial crime compliance technology for banks and financial institutions, providing the Anti-Money Laundering Suite that uses machine learning to improve transaction monitoring accuracy, reduce false positive alert rates, and enhance suspicious activity detection across financial transaction data. The Singapore company also operates the Typology Repository, a community knowledge base of money laundering typologies that informs its ML model training.\n\nThe company raised approximately $20 million in venture funding from investors including Illuminate Financial, Jungle Ventures, and SBI Investment. Tookitaki serves regulated financial institutions in Asia-Pacific and the Middle East that face increasing AML regulatory pressure and high false positive rates from traditional rule-based transaction monitoring systems that generate large volumes of alerts requiring manual review. Reducing false positive rates is the primary commercial value proposition, as financial institutions spend billions annually on compliance analyst time reviewing unproductive alerts.\n\nTookitaki competes in the AML technology market against NICE Actimize, SAS AML, and Oracle Financial Services, as well as newer AI-native AML vendors including Quantexa and Featurespace. Its community typology repository approach differentiates it by incorporating human expert knowledge about money laundering methods into its ML training process, rather than relying exclusively on historical transaction labels that may miss novel laundering patterns. The Singapore base gives Tookitaki access to the concentrated regional banking hub and the MAS regulatory framework that supports fintech innovation.