Agentic AI unlocks powerful new automation capabilities for modern organizations, allowing AI agents to reason, plan, and execute complex workflows independently. But full autonomy introduces significant challenges: decisions may lack critical context and hallucinations can lead to costly errors. Meanwhile, organizations remain accountable for every action an AI takes.

Duet addresses this problem by combining the speed and scale of agentic AI with structured human oversight. It embeds Human-in-the-Loop (HITL) checkpoints into AI workflows, ensuring sensitive or high-stakes decisions are reviewed, approved, or refined by human experts before execution. This hybrid approach delivers the efficiency of Agentic AI while maintaining trust, compliance, and alignment with organizational goals.

Duet accelerates production‑grade AI agents by combining AWS Bedrock AgentCore with a HITL approval workflow. With Duet, you can confidently deploy secure, auditable agents in your VPC, integrate with your existing data stores, and route sensitive decisions through Step Functions and Lambda for human review.

Key Features

Plug‑and‑Play Agents: Install certified MCP or A2A agents and tools from AWS Marketplace directly into your VPC.

Human‑in‑the‑Loop Approval: Out‑of‑the‑box Step Functions workflow routes proposed actions to human reviewers via Lambda, logging approvals/rejections in DynamoDB.

Serverless AgentCore Runtime: Leverage Bedrock AgentCore’s low‑latency, auto‑scaled runtime, memory, tools, and governance modules.

Secure Data Access: Fine‑grained Identity & Access Management (IAM), optional Bedrock Guardrails, and private subnet deployment keep PII/PHI on‑premise.

Prompt Management: Centralized prompt templates, versioning, and governance ensure consistent, auditable agent interactions.

Multi‑Channel Notifications: Integrate with Slack or Microsoft Teams for real‑time approval requests and audit trails.

Observability & Audit: Full telemetry via CloudWatch/OpenTelemetry; immutable audit logs in DynamoDB for compliance.

Example Use Cases

Customer Experience: Agents draft responses, but humans approve before sending in sensitive industries (finance, healthcare).

Knowledge Workflows: AI autonomously researches and summarizes, but humans verify final deliverables.

Operational Decisions: Agents execute IT or business workflows, but human reviewers approve any changes that could be irreversible.

Regulated Industries: Human oversight ensures AI decisions meet compliance standards (HIPAA, GDPR, SOC2).