Whalesbook
Pine Labs has launched a new AI-based UPI payment protocol, P3P, built on NPCI’s Reserve Pay framework. This system enables AI agents to execute transactions autonomously based on user rules. Digital gold platform Gullak has initiated the first pilot, aiming to automate investment decisions.
What Happened
Pine Labs has introduced a new payment technology branded as the Pine Labs Payment Protocol (P3P). This system is designed to enable agentic UPI transactions, where artificial intelligence agents carry out purchases on behalf of users without manual input. The solution is built upon the Reserve Pay framework provided by the National Payments Corporation of India (NPCI), which allows for delegated and automated payment mandates. Digital gold platform Gullak is the first partner to integrate this system, allowing users to set specific conditions—such as buying gold when prices reach a certain level—that the AI agent executes automatically.
The Technology Behind the Shift
Agentic payments represent a move toward autonomous commerce. In a traditional transaction, a user must manually initiate the payment, authenticate it, and approve the amount. Under this new protocol, a user sets the parameters once, and the software agent monitors the market or app interface to complete the transaction when the conditions are met. This is aimed at use cases where speed and timing are essential, such as locking in a price for a flash sale or executing a pre-planned investment, without requiring the user to be physically present at the moment of the transaction.
Competition and Market Approaches
The Indian digital payments sector is seeing a clear divide in how companies are adopting this AI-driven automation. Competitors, such as Razorpay, have also entered the agentic payments space. However, their approach differs slightly from the model Pine Labs is proposing. While Pine Labs is positioning its solution for fully autonomous transactions, other market players are emphasizing a need for human confirmation at the final step of the payment process. This 'human-in-the-loop' approach is designed to give users more control over complex transactions, such as booking tickets where variables might change unexpectedly.
Business and Regulatory Considerations
For the broader fintech ecosystem, the introduction of AI-led payments brings both efficiency and new challenges. Automating payments reduces friction, which can increase the volume of transactions for merchants. However, this also introduces risks related to unintended transactions. If an AI agent executes a purchase based on an error in logic or a sudden market shift, the liability and reversal process remain key concerns for both platforms and regulators. The Reserve Bank of India (RBI) and NPCI have generally maintained a cautious stance on consumer protection in digital payments, meaning that the scalability of these fully autonomous agents will likely depend on their ability to prevent fraud and errors.
What Stakeholders Should Watch
Investors and market participants should monitor how widely these tools are adopted beyond the current pilot phases. Key monitorables include the feedback from early users regarding security and ease of use, as well as any official guidelines released by the NPCI regarding the scope of autonomous AI agents in financial transactions. Additionally, the willingness of major retailers to integrate these systems—beyond the initial partnerships—will determine the long-term impact of this technology on the digital payments revenue pool.