Paystro Agentic Banking Assistant
Client
Paystro
Partner
Marlocks Technologies
Focus
Agentic AI
Overview
Paystro is a zero-fee international payments platform that faced significant operational bottlenecks as its transaction volume grew. Reliance on human-led support resulted in high operational costs, slow response times for routine inquiries, and an inability to provide 24/7 assistance to its expanding international user base.
Marlocks Technologies implemented a context-aware Agentic Banking Assistant on a serverless AWS architecture — combining intent recognition, retrieval-augmented generation, session persistence, and intelligent escalation into a single cohesive system.
The Problem
High operational costs from human-led support at scale
Slow response times for routine customer inquiries
No 24/7 support capability for an international user base
Growing transaction volume with no scalable support infrastructure
The Solution
Amazon Bedrock — Intent recognition powering accurate understanding of user queries
RAG Pipeline + OpenSearch — Knowledge retrieval ensuring responses are grounded in Paystro's actual policies and data
Amazon DynamoDB — Session context persistence enabling coherent multi-turn conversations
Amazon SNS Escalation — Human intervention triggered automatically when AI confidence is low
Projected Results
| Metric | Outcome |
|---|---|
| Intent Identification Accuracy | 90%+ |
| Support Ticket Volume Reduction | 25–35% |
| Concurrent Sessions Supported | 10,000+ |
| Response Time | Under 1.5 seconds |
| Target Customer Satisfaction | 85%+ |
Key Lessons Learned
Contextual continuity is critical for user trust in AI banking:
Maintaining session context across turns — and integrating direct action fulfillment via real-time API calls — is what separates a trusted banking assistant from a glorified FAQ bot.
Enterprise-grade serverless removes the scalability ceiling:
Serverless infrastructure meets both security and scalability requirements without increasing manual overhead, making it the right foundation for high-volume fintech workloads.