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Paytia Shields Card Data From AI Sales Agents

Daniel HartleyDaniel Hartley16 July 2026656 words
Paytia Shields Card Data From AI Sales Agents

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At a Glance

  • Paytia's new Conversational & AI Payments service keeps card data out of AI chat logs and language model context windows
  • The tool, built on Paytia's Capture Assist API, isolates payment capture from the AI agent entirely, addressing a PCI DSS compliance gap
  • Paytia has processed over £400 million in payments since 2020 and holds PCI DSS Level 1 certification

Paytia Ltd has launched a payment capture service designed to stop AI agents from ever seeing a customer's card number. The London-based payments company unveiled Conversational & AI Payments on July 15, 2026, built on its existing Capture Assist API. The service targets a compliance gap that has opened as businesses rush AI agents into phone and chat channels faster than security teams can vet them.

Closing the AI Payment Gap

The core problem Paytia is addressing is straightforward: when an AI agent takes a payment, the card number typically passes through the language model's context window. From there it can end up stored in call recordings, chat transcripts, or even training data — all of which sit outside standard PCI DSS controls designed for human-operated payment systems.

Capture Assist works by stepping in at the payment moment. Rather than the AI handling the card number itself, the customer enters payment details either through a hosted form or by phone keypad, isolated from the AI system entirely. Paytia processes the transaction on its PCI DSS Level 1 SecureFlow platform and returns only a token and a result to the bot, which then resumes the conversation.

The isolation extends beyond card numbers. Paytia says the same approach covers bank account details, passport numbers, and national insurance numbers — any sensitive data a business process needs to collect during an automated interaction.

"If there's an AI in the loop, this is the only safe way to take a payment. A card number should never sit in a chat log or an LLM's context — but that's exactly where it ends up in most of the AI agents being built right now. We draw a hard line around the card. The bot runs the conversation, we hold the sensitive data, and the two never mix."

— Curtis Nash, CEO at Paytia

How the Integration Works

For telephone-based AI agents, Paytia connects via SIP in one of two configurations. It can sit in front of the bot for full isolation throughout the call, or it can conference in only when payment is due, triggered by a unique call ID embedded in the SIP header. Chat-based agents capture payments through what Paytia calls Advanced Payment Links.

Existing Paytia customers can activate the service through a configuration change rather than negotiating a new contract, according to the company. The service is underpinned by a Data Protection Agreement in which Paytia acts as the appointed data processor, with defined terms governing how sensitive data is captured, retained, and deleted. The company states card data is never logged or used to train models.

The launch reflects a broader tension facing enterprises deploying conversational AI: automation is advancing faster than the compliance frameworks built to govern payment card data. As more customer service and sales functions shift to AI agents handling phone and chat interactions, the question of where sensitive data physically travels — and who is liable if it leaks — becomes a live commercial risk rather than a theoretical one.

Paytia holds PCI DSS Level 1 and Cyber Essentials Plus certification and says it has processed more than £400 million in payments since 2020. The company serves clients across the UK, US and Canada from offices in London and New York.

Conversational & AI Payments is now available to Paytia's client base. The launch signals growing pressure on payment providers to build safeguards specifically for AI-mediated transactions, rather than retrofitting older compliance tools. How quickly rivals respond with comparable isolation mechanisms may shape how enterprises structure AI deployments handling financial data going forward.

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