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How P3P works: The user sets up a UPI mandate, a standing instruction that pre-approves payments up to a fixed limit, and the AI agent transacts within those bounds. The protocol combines three parts:
The user approves the mandate once by scanning a code in their UPI app, after which the agent’s requests debit against the reserved funds without fresh approval. The user can cancel the mandate at any time.
Who is live on it:
P3P is currently live on UPI ReservePay only. Pine Labs says cards, net banking, wallets and Equated Monthly Instalment (EMI) options are on its roadmap. Its developer documentation separately lists stablecoins, cryptocurrencies pegged to stable assets such as the US dollar, as a future payment rail.
How P3P differs from Razorpay’s agentic payments: Razorpay has offered agentic UPI payments since October 2025, first with the National Payments Corporation of India (NPCI) and OpenAI on ChatGPT, and later with Anthropic on Claude. In those cases, the payment still requires the user’s final consent before completion, even though the shopping and checkout happen inside a specific AI assistant such as ChatGPT or Claude.
P3P uses the same underlying UPI mandate mechanism, but operates as a standalone protocol with a common set of rules that any software can plug into, allowing any AI agent on any app or website to use it instead of tying it to one assistant.
Pine Labs’ prior agentic work: This is not Pine Labs’ first move into agentic payments. MediaNama has covered its earlier talks with NPCI on autonomous UPI payments through its Model Context Protocol (MCP) server, a tool that connects AI systems directly to its payment infrastructure, and its subsidiary Setu’s agentic bill-payments service on Claude and ChatGPT. The company has stayed quiet on privacy questions analysts raised about what data AI providers receive versus what Pine Labs retains, and whether the company stores prompts and transaction details or uses them to train AI models.
Pine Labs positions P3P as a consumer-controlled framework where users predefine spending limits, merchants, triggers and validity conditions, while AI agents only execute transactions within those pre-approved boundaries. However, the system still raises unresolved regulatory, security and liability questions. We outline some of them below:
1. Is Pine Labs using the UPI mandate framework for a purpose it was not built for? A UPI mandate, the standing instruction that pre-approves payments, originally supported recurring, scheduled payments to a known merchant: a monthly subscription, a Systematic Investment Plan (SIP) into a mutual fund, or an Equated Monthly Instalment (EMI) on a loan. It did not originally support one-off, event-triggered purchases that an AI agent independently decides and executes.
With P3P, AI agents can buy gold whenever a price condition is met or grab a flash sale the moment it goes live, stretching the mandate well beyond its original design. Pine Labs has not publicly stated whether NPCI created or approved a separate framework for autonomous AI-triggered purchases under UPI mandates.
2. How does P3P square with RBI’s rule that every payment needs an extra security check? The Reserve Bank of India (RBI), in its Digital Payments E-Mandate Framework, 2026, requires that setting up any mandate be verified using Additional Factor of Authentication (AFA), an extra security step such as a one-time password (OTP) or a UPI Personal Identification Number (PIN). Normally, every UPI payment requires the user to enter their UPI PIN at the moment of paying. P3P removes that step at the point of payment: the user approves the ReservePay mandate once, and the AI agent then debits the reserved funds without requiring a PIN each time.
Under the RBI framework, banks can process recurring transactions up to Rs 15,000 without Additional Factor Authentication (AFA) once a user sets a mandate, but they still require AFA for transactions above Rs 15,000. It is not clear how P3P handles a single agent-initiated payment above that limit, given there is no human present to authenticate it.
3. Who is responsible if an AI agent makes a wrong or unauthorised payment? MediaNama’s coverage of Razorpay’s agentic payments launch found no agreement in the industry on who is liable when an AI agent pays incorrectly. Razorpay said agentic shopping “does not rewrite the rules of commercial liability”, meaning the merchant handles a wrong order and Razorpay covers payment-security failures.
Pine Labs markets P3P as producing a cryptographically verifiable receipt for each transaction, which it says supports dispute resolution, but it has not stated who actually bears liability when an agent pays in error. The question matters most for high-value payments that users cannot reverse, such as locking in a down payment before stock runs out.
4. What data does P3P share with AI providers, and on what terms? When an analyst asked what transaction data goes to AI providers versus what stays with Pine Labs, CEO Amrish Rau declined to answer. P3P now extends from bill payments to autonomous purchase decisions, which means more data about what a user buys and when. Whether the user’s prompts, transaction records and spending behaviour are stored, passed to AI providers such as OpenAI or Anthropic, or used to train their AI models, has not been disclosed.
5. Does the stablecoin roadmap clash with India’s position on crypto? Pine Labs’ developer documentation lists stablecoin as a future payment rail for P3P. India does not recognise cryptocurrencies as legal tender, and the Reserve Bank of India (RBI) has repeatedly raised concerns about the financial stability and monetary risks posed by private cryptocurrencies. How Pine Labs intends to settle agentic payments in stablecoin within India’s regulatory environment, and whether it would receive regulatory clearance to do so, is unclear.
MediaNama has reached out to Pine Labs with questions. This copy will be updated when we receive a response.
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