In line with its bid to modernise its digital payments offerings, fintech major Pine Labs invested about ₹24 Cr on AI and research & development initiatives in the fiscal year FY26.

Over FY26, the fintech company invested ₹20 Cr in strengthening its AI capabilities, upgrading its technology infrastructure and automating customer-facing processes. 

It spent another ₹4 Cr on enterprise-wide technologies such as model context protocol (MCP), retrieval-augmented generation (RAG), among other AI-based automation tools.

In its FY26 annual report, the company outlined that it successfully deployed email AI agents as well as PineOne Chat AI Agent to automate customer support, an AI-powered scheme configuration tool to streamline offer enablement and an AI Virtual Employee platform for multi-functional agentic tasks.

“The company continued to invest in AI agents, customer-facing chatbots, Model Context Protocol-enabled self-service platforms and Retrieval-Augmented Generation-powered operational intelligence solutions,” the report added. 

The company claims that its investments have begun yielding results, with it reducing its software testing cycle times by more than 95%. Pine Labs further estimates that AI initiatives have now increased developer productivity by 25% and cut initial incident analysis time by 80%. This has helped autonomous AI agents shoulder the development of nearly 89% of all new code changes at the firm over the past two quarters, modifying more than 1.5 Mn lines of code. 

Building AI Applications Beyond The Organisation

Beyond adopting AI for internal uses, Pine Labs also mentioned that it has launched some consumer and merchant facing AI tools, such as an autonomous agentic payments protocol, P3P, built atop of UPI. 

The company described P3P as “a compliance-first architecture where buyer and seller agents discover, negotiate, and complete transactions autonomously within established regulatory guardrails.”

It also rolled out SignalIQ, an automated bank statement analyser and underwriting engine, which tracks UPI transactions to predict financial stress. The company claims that SignalIQ has processed over 50,000 loan requests within weeks of launch to deliver real-time credit intelligence for lending partners. 

“We are no longer focused solely on adopting AI; we are helping shape the standards, protocols and infrastructure that will underpin the next generation of AI-native commerce,” Pine Labs said. 

How Pine Labs Is Ensuring AI Safety And Security

Pine Labs has deployed AI across its cybersecurity operations, including false-positive analysis, zero-day threat alerts and automated code scanning.

Its AI agents operate within role-based permissions, with audit trails, continuous monitoring and centralised oversight through its Agentic HQ governance layer.

It has also rolled out automated vulnerability remediation and an IT general controls audit dashboard, along with an AI-based threat intelligence agent for security alerts and monitoring.

On the financial front, Pine Labs turned profitable for the full fiscal year in FY26, reporting a consolidated net profit of ₹112.5 Cr. Operating revenue rose 19% YoY to ₹2,710.6 Cr.

In Q1 FY27, net profit jumped more than 4X YoY to ₹19.6 Cr, although it fell 67% QoQ. Operating revenue grew 20% YoY and 5% QoQ to ₹736.9 Cr.

The fintech company’s platform processed 201 Cr transactions worth ₹4.2 Lakh Cr in GTV during the June quarter.

Shares of Pine Labs ended today’s trading session 3.84% higher at ₹163.50 apiece on the BSE.

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