Sift vs Tookitaki

Sift has a disclosed valuation of $1B, while Tookitaki's valuation is not publicly available, making a direct size comparison difficult. Sift employs 400 people.

Sift has raised more in total funding at $162M, compared to Tookitaki's $20M — a gap of $142M. Combined, the two companies have completed 5 known funding rounds.

Sift holds the higher Awaira Score at 61/100, compared to Tookitaki's 45/100. The Awaira Score is a composite metric factoring in valuation, funding, stage, team size, and market presence — a 16-point gap that reflects meaningful differences in scale or traction.

Sift was founded by Jason Tan in 2011. Tookitaki was founded by Abhishek Chatterjee in 2014. Visit each company's profile on Awaira for a full founder biography.

Sift: Sift is an AI-powered fraud prevention and digital trust platform founded in 2011, headquartered in the USA. The company specializes in identifying and preventing fraudulent transactions, account abuse, and payment fraud for digital commerce businesses. Its core platform uses machine learning algorithms to analyze user behavior patterns, transaction data, and device information in real-time, enabling merchants and financial services companies to distinguish between legitimate and fraudulent activity. Sift's primary products include fraud detection APIs, chargeback management tools, and account abuse prevention systems. The platform processes billions of transactions and events annually, building predictive models from this data to improve detection accuracy over time. The company serves e-commerce platforms, payment processors, financial institutions, and subscription services globally. With $162M in total funding and a $1.0B valuation, Sift operates at Series E stage, indicating substantial market traction and investor confidence. The company competes in the broader fraud prevention and fintech security sector alongside players like Stripe Radar, PayPal's fraud tools, and specialized fraud detection vendors. Its competitive positioning centers on machine learning sophistication, real-time processing capabilities, and integration flexibility for digital commerce ecosystems. Sift has maintained consistent growth since its inception, expanding its customer base and product capabilities to address evolving fraud threats in digital commerce environments. Sift combines behavioral analytics with machine learning to provide real-time fraud detection at scale for digital commerce platforms. Tookitaki: 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.

Sift was founded first in 2011, giving it 3 years of additional market experience. Tookitaki was founded later in 2014. In AI, even a year or two of head start can translate into significantly more training data, customer relationships, and institutional knowledge.

Sift has approximately 400 employees, while Tookitaki has approximately 100-500. A larger team often signals higher revenue or venture backing, but in AI, smaller teams are increasingly capable of building at scale.

Yes, Sift and Tookitaki are direct competitors — both operate in the AI Finance space and likely target overlapping customer segments. This comparison is especially relevant for buyers evaluating both platforms.