Indian fintech giant Pine Labs says it has scaled engineering output without increasing headcount, attributing the gains to expanded use of artificial intelligence across its development lifecycle.
In a post on X, CEO Amrish Rau shared internal data showing that the company’s engineering teams have shifted from experimenting with AI tools to deploying them in production workflows.
“In the last 28 days, our engineering teams have meaningfully scaled AI adoption across the development lifecycle—moving from experimentation to real production impact,” Rau wrote.
He revealed that during this period, more than 1.3 million lines of code were changed with AI assistance, with agents contributing to approximately 89% of code changes.
He added that engineers have built in-house agents for design, coding, pull request reviews, and functional testing. These agents are integrated with tools such as Jira, Confluence, GitHub, and Figma through APIs and Model Context Protocol connections, enabling them to execute tasks across systems rather than function as standalone coding assistants.
He also shared the same statistics from the GitHub dashboard.
The disclosure comes amid broader industry debate about whether AI tools will meaningfully reduce hiring needs in software development or simply augment existing teams. “AI is no longer just a productivity tool for us—it’s becoming part of how we design, build, test, and ship products,” Rau said.
Recently, Pine Labs announced a collaboration with OpenAI to embed the latter’s APIs into the core of its merchant infrastructure, positioning the move as a shift toward what it calls “agentic commerce”.
By embedding OpenAI’s models into its stack, Pine Labs aims to build a reasoning layer capable of interpreting context and making constrained decisions across high-volume payment environments.
Rau said the collaboration is intended to transform Pine Labs’ infrastructure from a passive transaction processor into an active intelligence layer that drives efficiency and growth for merchants.
Under the proposed architecture, AI agents would be able to perform tasks such as negotiating supplier terms, optimising cross-border settlement cycles, and managing recurring bill payments, while operating within predefined compliance and security boundaries. Pine Labs said these workflows will run within its enterprise-grade security framework, with data isolation, encryption, auditability, and human oversight where required.
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