Pints AI Autothought

Pints AI is a Singapore-based company building AI agents for regulated financial institutions, according to KrASIA's June 2026 report. It targets banks, insurers and asset managers that need to automate underwriting, claims and onboarding while keeping results traceable for regulators.

Its Autothought framework is built from six capabilities: Intake, Extract, Align, Govern, Report and Assure, and agents combine the modules a process needs. It integrates with legacy and modern systems and runs on-premise, in private cloud or hybrid, with all processing kept on the institution's infrastructure. Every agent decision is traceable through a Source Attribution Neural Network (SANN) that produces an audit trail, and uncertain outputs go to human review. Clients are live in Singapore, Hong Kong, India and Thailand.

• Intake and Extract: bring in data from any source and pull out structured information.
• Align: standardise extracted data to the institution's systems.
• Govern and Report: apply business rules and generate outputs.
• Assure: validate results to auditable standards.
• SANN audit trail: traces each agent decision to its sources.
• Flexible deployment: on-premise, private cloud or hybrid, with data kept in the customer's environment.

Vietnamese insurers can automate claims intake and adjudication with traceable decisions. Banks can speed up customer onboarding and document checks while keeping data on-premise. Asset managers can standardise reporting workflows with audit trails.

The FAQ states most institutions reach production in as little as 21 days, depending on workflow complexity. Data is not migrated to external servers. Audit trails and human review of uncertain outputs support regulatory expectations. There is no fixed minimum deal size, and engagements are scoped around specific workflows.

Financial regulators in Asia expect explainability and audit trails for AI used in underwriting and claims. Banks and insurers prefer deployments that keep data inside their own infrastructure. Vietnamese insurers and banks modernising legacy back offices face the same requirements.

Singapore-based per KrASIA (16 June 2026). USD 5.6 million pre-Series A led by Tin Men Capital. The 1.5 Pints small language model is open-sourced under the MIT licence. Clients live in Singapore, Hong Kong, India and Thailand.