Tookitaki vs Thought Machine

Thought Machine has a disclosed valuation of $2.7B, while Tookitaki's valuation is not publicly available, making a direct size comparison difficult. Thought Machine employs 500-1000 people.

Thought Machine has raised more in total funding at $563M, compared to Tookitaki's $20M — a gap of $543M. Combined, the two companies have completed 5 known funding rounds.

Thought Machine leads with an Awaira Score of 85/100, while Tookitaki sits at 45/100. That 40-point gap reflects real differences in funding, scale, and traction — it's not a vanity metric.

Tookitaki was founded by Abhishek Chatterjee in 2014. Thought Machine was founded by Paul Taylor in 2014. Visit each company's profile on Awaira for a full founder biography.

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 advancement. Thought Machine: Thought Machine builds Vault, a cloud-native core banking platform that uses a smart contract programming language to define financial products as configurable code rather than hardcoded legacy software. The London company targets tier-one and tier-two banks seeking to replace decades-old mainframe core banking systems with a modern, API-first platform that can deploy on any major cloud provider and enable rapid product iteration.\n\nThe company raised approximately $563 million including a $160 million Series D led by Temasek, with Intesa Sanpaolo and Standard Chartered among its strategic investors, giving it a valuation of approximately $2.7 billion. Thought Machine counts Lloyds Bank, Curve, SEB, and JPMorgan among its enterprise clients, with live deployments processing significant volumes of retail and commercial banking transactions on its cloud-native infrastructure.\n\nThought Machine operates in a core banking replacement market estimated at over $10 billion annually, competing with Temenos, Finacle, and Mambu for bank transformation budgets. Its product architecture is considered technically differentiated by banking analysts, as the smart contract approach to product configuration allows banks to define entirely novel financial products without custom development work. The company faces the long sales cycles and regulatory validation requirements inherent in replacing critical banking infrastructure, but its growing client roster of established financial institutions validates its position as a credible replacement for legacy core banking vendors.

Both Tookitaki and Thought Machine launched in 2014. Same year, but even a few months' head start matters in AI — early movers lock in data, talent, and customer relationships fast.

Tookitaki has about 100-500 employees; Thought Machine has about 500-1000. A bigger team usually means more revenue or heavier VC backing, but in AI, small teams can build at massive scale.

Yes — they're direct rivals. Both Tookitaki and Thought Machine compete in AI Finance, targeting many of the same buyers. If you're evaluating one, you should be looking at the other.