India, May 2026 – Dailoqa, a specialist in agentic AI for financial services, announced the successful deployment of AU Small Finance Bank’s first AI-native Loan Origination System, built on the enterprise-grade Broccoli™ platform. The deployment, delivered in partnership with Amazon Web Services (AWS), marks a significant milestone in AU Small Finance Bank’s journey to become a fully AI-native bank.
From digital workflows to intelligent banking
AU Small Finance Bank’s new Loan Origination System replaces siloed, product-specific, process-tied legacy and digital systems with a context-specific, hyper-personalised sales and servicing platform. By removing fixed digital workflows, the bank’s teams are freed to focus entirely on managing the financial wellbeing of their customers, rather than managing software.
The enterprise-grade Broccoli™ platform, Dailoqa’s proprietary multi-agent AI orchestration system, is purpose-built for the regulatory complexity of financial services. The approach is explicitly platform-driven: no standalone PoCs, no agents layered onto legacy digital architecture. The result is a drastic reduction in change cycles, a step change in cost of ownership compared to traditional SaaS digital platforms, elimination of technical debt, and rapid reskilling of colleagues to become AI enablers.
What is being built?
With the Loan Origination System now live, the partnership is moving at pace. Full-scale implementation for commercial banking customers and mortgages is underway. A model-agnostic multilingual platform for customer service is being deployed alongside an AI-driven engagement platform, with plans to move up to 25% of outbound calls to the platform. To sustain this momentum and drive the talent transformation required, AU Small Finance Bank is establishing an AI Centre of Excellence, supported by Dailoqa and AWS.
Sanjay Agarwal, CEO & MD, AU Small Finance Bank says, “Badlaav Humse Hai is not our slogan, it is our spirit and DNA. Our vision is to combine the intelligence of our colleagues with intelligent systems, to create the Combined Intelligence of our Enterprise. We have engineered and implemented an agentic AI platform designed specifically for the complexities of our bank and our compliance requirements. Earlier this month, we successfully deployed our first AI-native Loan Origination System and we are not stopping here. Change is truly in the air and the AU Small Finance Bank is just getting started.”
Piyush Singh, Co-Founder, Dailoqa remarks, “When a CEO moves past the mystique of AI to ask how it can enable the organisation’s true purpose, you know you have found the right partner. The leadership at AU Small Finance Bank have a clarity of vision that makes this kind of transformation possible. Enterprise-scale AI adoption does not happen through pilots or point solutions. It happens through a platform-first approach that is regulation-first by design, and through leadership that is willing to act. That is what we are building together.”
Sandeep Dutta, President, AWS India and South Asia states, “Combining AU Bank’s philosophy ‘Badlaav Humse Hai’ with AWS India’s vision of ‘Building from India for India and the World’ is starting to show real results. Together, we have engineered and deployed an agentic AI platform purpose-built for the regulatory complexity and scale of Indian banking. This is not a pilot. AU Bank went live with their first AI-native Loan Origination System, eliminating rigid digital workflows and freeing their teams to focus entirely on their customers’ financial wellbeing. I am incredibly proud of what our teams have built together.”
The partnership
The partnership brings together complementary capabilities across infrastructure and intelligence. AWS provides secure, scalable, compliance-ready infrastructure for regulated financial services, with Amazon Bedrock powering generative AI at scale and a governance architecture that allows the bank to move quickly without compromising on compliance. Dailoqa brings specialisation in agentic AI for banking, orchestration of complex multi-step processes, and a model-agnostic framework built to evolve as the technology evolves.
