Introduction

The payments industry is undergoing a seismic shift as agentic AI—systems capable of autonomous reasoning and action—redefines how transactions are processed, disputes are managed, and customer experiences are enhanced. At lowtouch.ai, we see this as a validation of our philosophy: agentic AI is the future of enterprise automation, and no-code platforms like ours are the key to making it accessible, compliant, and privacy-first.

PayPal Agent Toolkit: Tokenized Credentials and Deep Post-Payment Features

Announcement Date: 14 & 29 Apr 2025 (PayPal Dev Days)
Headline: “Let any AI agent plug directly into PayPal to handle the full commerce loop—pay, track, invoice, dispute”
Key Use Cases:

  • Pay for purchases and settle invoices
  • Track shipments in real time
  • Auto-manage subscriptions and inventory
  • Raise or resolve disputes

Key Features:

  • Existing PayPal Open Platform APIs plus new Model Context Protocol (MCP) & Agent-to-Agent workflow endpoints
  • One-time-password identity checks, PayPal fraud intelligence, embedded merchant verification
  • Tokenized credentials and agent-friendly endpoints

PayPal’s deep post-payment capabilities mirror lowtouch.ai’s MCP-powered integrations—but with our no-code UI, non-technical teams can assemble identical workflows without writing a single line of code.

Mastercard Agent Pay: Tokenization and User Controls

Announcement Date: 29 Apr 2025 (Global Press Release)
Headline: “New payment infrastructure for agentic commerce—autonomous AI assistants execute transactions on behalf of users”
Key Use Cases:

  • Birthday-party shopping concierge
  • SME sourcing overseas & virtual corporate card settlement
  • Retailer chat-bot for “best way to pay”

Key Features:

  • Agentic Tokens on Mastercard’s token & passkey stack, with programmable rules
  • Trusted-agent registration, on-device biometrics, user-set purchase permissions
  • Integrations with Microsoft, IBM Watson, BrainTree, Checkout.com

Mastercard’s focus on security and tokenization aligns perfectly with lowtouch.ai’s privacy-first, air-gapped deployments. Our guardrails (PII filtering, safety classifiers, HITL) layer an extra level of compliance on top of their biometric controls.

Visa Intelligent Commerce: Granular Spend Limits & Instant Global Acceptance

Announcement Date: 30 Apr 2025 (Visa Global Product Drop)
Headline: “Empower AI agents to deliver personalized and secure shopping experiences at scale”
Key Use Cases:

  • Booking flights & hotels within spend limits
  • Ordering weekly groceries automatically
  • Reserving restaurant tables & paying without exposing card data

Key Features:

  • AI-ready cards via Visa Payment Passkeys, with 5 APIs for auth, tokenization, spend-rules, risk signals
  • User-defined spend limits, MCC filters, real-time approval prompts
  • Visa AI fraud engine (blocked $40 B in 2024)

Visa’s granular controls are surfaced through lowtouch.ai’s vector-database–driven RAG and conversational UI, letting you build “grocery bots” or “travel concierges” entirely without code.

Comparative Analysis: Where lowtouch.ai Fits In

PayPal, Mastercard, and Visa each illustrate the shift toward agentic payments—with three common pillars:

  1. Autonomous Execution – agents handle end-to-end transactions.
  2. Security & Privacy – tokenization, fraud detection, trusted-agent controls.
  3. Seamless Integration – deep API ecosystems across CRM, ERP, cloud providers.

lowtouch.ai layers a no-code experience on top:

  • Drag-and-drop workflows for transaction, invoicing, dispute resolution
  • Air-gapped deployments ensure payment data stays on premise
  • Built-in guardrails & HITL review for high-risk actions

How lowtouch.ai Empowers Enterprises in the Payments Space

1. Autonomous Payment Processing
Deploy no-code agents that integrate with PayPal’s Agent Toolkit or Visa Passkeys to automate the full commerce loop: payments, tracking, invoicing, disputes.

2. Enhanced Customer Experiences
Build personalized shopping assistants by combining vector-search–driven user profiles with real-time spend rules—delivered via chatbots or in-app UIs.

3. Fraud Detection & Risk Management
Leverage external LLMs (e.g., Claude, Gemini) for advanced anomaly detection, layered on top of Mastercard’s on-device biometrics and Visa’s fraud signals.

4. Compliance & Auditability
Run all agents within your infrastructure to maintain GDPR, SOC 2, and PCI DSS compliance—complete with line-of-thought logs via OpenSearch & Grafana.

A Practical Example: Building a Payment Agent with lowtouch.ai

Use Case: Automate weekly grocery orders under Visa spend limits, with HITL approval for large transactions.

Step 1: Define Instructions
– Retrieve grocery list from SharePoint.
– Check spend limit via Visa API.
– If within limit, place order; otherwise trigger HITL via Slack.

Step 2: Configure Integrations
– Connect Visa’s Payment Passkeys with OAuth2.
– Hook SharePoint via prebuilt connector & MCP.
– Store user preferences in the vector database.

Step 3: Implement Guardrails & HITL
– PII filter for outputs.
– Safety classifier to catch injections.
– HITL for orders above threshold.

Step 4: Schedule & Monitor
– Schedule via our conversational scheduler.
– Observe logs in OpenSearch/Prometheus dashboards.

Step 5: Scale
– Extend to travel bookings, vendor payments, and multi-agent orchestration—all via the same no-code interface.

Conclusion: The Future of Agentic AI in Payments

The initiatives from PayPal, Mastercard, and Visa demonstrate the dawn of agentic AI in payments. With lowtouch.ai, enterprises gain a no-code, privacy-first platform to build, secure, and scale these capabilities instantly—no heavy development required.

Ready to transform your payment workflows?
Connect with us at lowtouch.ai or on LinkedIn to see a demo and accelerate your agentic AI journey.

About the Author

Rejith Krishnan

Rejith Krishnan is the Founder and CEO of lowtouch.ai, a platform dedicated to empowering enterprises with private, no-code AI agents. With expertise in Site Reliability Engineering (SRE), Kubernetes, and AI systems architecture, he is passionate about simplifying the adoption of AI-driven automation to transform business operations.

Rejith specializes in deploying Large Language Models (LLMs) and building intelligent agents that automate workflows, enhance customer experiences, and optimize IT processes, all while ensuring data privacy and security. His mission is to help businesses unlock the full potential of enterprise AI with seamless, scalable, and secure solutions that fit their unique needs.

About lowtouch.ai

lowtouch.ai delivers private, no-code AI agents that integrate seamlessly with your existing systems. Our platform simplifies automation and ensures data privacy while accelerating your digital transformation. Effortless AI, optimized for your enterprise.

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