How AgentFlo built AI sales agents with Amazon Bedrock AgentCore – Part 2

This article details how AgentFlo built production-scale AI sales agents using Amazon Bedrock AgentCore, achieving measurable business results through trust, reliability, and scalable architecture.

• Three-layer guardrails enforce trust: Fargate prompt injection detection, AgentCore Gateway Cedar policies, and post-turn privacy filters
• Stateful sessions via AgentCore runtime and DynamoDB maintain context across multi-day customer journeys without hallucination
• Semantic product discovery using vector embeddings enables natural language search ("the pink one") without keyword dependency
• AgentCore Observability provides end-to-end tracing for debugging, cost attribution, and performance monitoring per merchant
• Business results: +12% net revenue uplift, +40% engagement, +15% conversion rate, +8% average order value over 90-day deployment
• Roadmap includes real-time voice agents via BidiAgent and WebRTC, server-side tool execution reducing latency ~30%, and modular MCP integrations

By combining stateful sessions, deterministic policy enforcement, and serverless infrastructure, AgentFlo scales from normal traffic to 50x spikes while maintaining enterprise security and data reliability.