What's moving at Pints AI - funding, product, and field intelligence from regulated AI deployments.
Singapore, 15 June 2026
We've raised US$5.6 million (S$7.2 million) in our pre-Series A round, led by Tin Men Capital, with SBI Ven Capital as co-lead. SEEDS, NTUitive, SUTD Venture Fund, and Tenity also participated. The round fuels our expansion across APAC and the Middle East, deepens our regulatory governance capabilities, and grows our engineering team.
In under two years, 12 financial institutions across Singapore, India, Hong Kong, and the United States have saved a combined US$10 million across live Autothought deployments spanning a range of use cases, including cutting underwriting times by 40% and onboarding by 70%.
Autothought connects directly to the core systems banks and insurers run on, automates slow manual processes like underwriting, claims, and onboarding, and produces a full audit trail for every AI-assisted decision.
Most AI projects inside regulated institutions never make it past the trial stage. AI-assisted decisions in underwriting, claims, or credit assessment have to be traceable and defensible to a regulator. That means connecting to decades-old internal systems and satisfying data sovereignty rules across multiple jurisdictions.
The gap is real. A February 2026 Deloitte study found that while 72% of businesses in Singapore plan to deploy AI agents, only 14% have governance models mature enough to manage the risks.
Autothought closes that gap with an agent orchestration framework that matches each task to the right model, from our own compact small language models (SLMs) to frontier models like Claude and open-source options, delivering enterprise-grade accuracy at significantly lower cost. We also send our own engineers to work directly inside each institution, connecting Autothought to the core systems where the data and risk sit.
Autothought is built to meet the compliance and audit requirements of the Monetary Authority of Singapore, the Reserve Bank of India, the Hong Kong Monetary Authority, and other regional regulators. Every AI-assisted decision can be traced to its source data, and uncertain outputs are flagged for human review.
The investment lands as Singapore expands its national AI and frontier tech agenda. In Budget 2026, the government committed S$37 billion to frontier technology development through 2030, naming AI in finance as one of four priority sectors. Singapore's Agentic AI Governance Framework, launched in January 2026, sets global standards for exactly the kind of auditable, traceable AI deployment Autothought was built around.
The world's largest AI companies build the foundation models. But frontier capability and production deployment inside regulated institutions are two fundamentally different problems, and that's where we sit: the local layer that understands the regulatory constraints, legacy infrastructure, and compliance demands of Asian financial institutions, and turns frontier capability into real operational outcomes.
This capital brings our deployment model to regulated institutions across new markets. We're expanding the engineering team, building out governance and audit capabilities for new regulatory environments, and developing Autothought Studio, a set of tools that lets institutions' own engineering teams build and manage AI applications internally.