Q2 Adds AI Code Generation to Banking Platform Development
Q2 Holdings announced Q2 Code on Friday, a development environment that uses generative AI to help financial institutions and partners build extensions for its digital banking platform. The tool converts natural language prompts into code that complies with Q2's software development kit, cutting development time from weeks to days.
Q2 Code integrates Anthropic's Claude through Amazon Bedrock, giving developers AI assistance within a governed environment designed for regulated financial services. Developers can generate, test and refine code without manually assembling workflows or navigating documentation.
How it works for development teams
The tool sits inside Q2 Innovation Studio, where financial institutions already build custom integrations and fintech partnerships. Q2 Code accelerates that process by generating code aligned to platform APIs, patterns and best practices from the start.
Rather than writing boilerplate or consulting documentation repeatedly, developers describe what they need in natural language. The AI produces working code ready for the Q2 platform, reducing friction between ideation and implementation.
Adam Blue, Q2's CTO, said the tool embeds AI directly into the SDK to drive faster innovation. "It will help banks, credit unions and partners build on Q2 faster while maintaining the trust, governance and resilience they require," he said.
Real-world testing underway
Mid-Hudson Valley Federal Credit Union will participate in Q2 Code's Early Access program, testing the tool in production scenarios. Jonathan Cilley, the credit union's SVP and Chief Information Officer, said the ability to move from idea to prototype faster creates opportunities to test and deliver more differentiated experiences.
Q2 is also using Q2 Code internally across product and engineering teams throughout the software development lifecycle. The company plans to expand the Early Access program throughout 2026.
For teams building on the Q2 platform, the tool reduces engineering constraints and acts as a force multiplier-allowing product leaders and platform managers to contribute to development without expanding headcount.
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