Rocket Close’s Supercharger: Automating Title Research with Agent AI

Rocket Close’s Supercharger, co-developed with AWS, is a practical solution that leverages agent AI to streamline title research operations. Traditional title research required manual searches across multiple systems, state guides, and county requirements, taking several hours per search.

Supercharger is built by combining Strands Agents SDK, Amazon Bedrock, Amazon Bedrock Knowledge Bases, and Model Context Protocol (MCP) tools. It utilizes the Anthropic Claude Large Language Model via Amazon Bedrock, with the flexibility to switch to different LLMs in the future.

(Source: Building Supercharger: How Rocket Close optimized title operations with agentic AI)

System Architecture and 6 Core Features

Supercharger consists of six interconnected features: conversational analysis, state-level title research support, API-based integration, guardrails and answer accuracy, logging and monitoring, and integrated data access.

In terms of security, it combines Amazon Bedrock Guardrails with row-level data permissions to prevent accidental access to customer confidential data. All conversations are logged with a complete audit trail, meeting compliance requirements. It integrates with Rocket Close’s operational database, providing access to order information, standard procedures, and state-level title research policies.

(Source: Building Supercharger: How Rocket Close optimized title operations with agentic AI)

New Feature of Amazon API Gateway: AgentCore Gateway Integration

Amazon API Gateway now supports REST APIs as targets for Amazon Bedrock AgentCore Gateway. This feature was added on December 2, 2025, enabling direct integration of agent AI systems with existing REST APIs.

API Gateway also supports private integration with Application Load Balancer, response streaming for REST APIs, and developer portal features. The developer portal provides a centralized location for customers to discover and test APIs, representing products or services to be shared as portal products.

To get started, refer to the “Add an API Gateway REST API as a target for Amazon Bedrock AgentCore Gateway” documentation in the AWS Console’s API Gateway section.

(Source: Document history - Amazon API Gateway)

Implementation Patterns for API Documentation

API Gateway provides comprehensive documentation features for REST APIs. You can create documentation parts for individual API elements, such as API entities, resources, methods, parameters, and responses.

Documentation can be performed through the API Gateway console, REST API, AWS SDK, and AWS CLI. You can also import and export documentation parts from external OpenAPI files. Created documentation can be associated with API stages, and stage-specific documentation snapshots can be exported to external OpenAPI files for distribution.

To share API documentation with developers, you can integrate with developer portals like ReadMe or SmartBear’s SwaggerHub.

(Source: Documentation for REST APIs in API Gateway - Amazon API Gateway)

Summary

  • Combining Strands Agents SDK and Amazon Bedrock enables the automation of complex business processes like title research using natural language interfaces.
  • Amazon API Gateway’s AgentCore Gateway integration allows direct connection of existing REST APIs as targets for agent AI systems, facilitating legacy system integration.
  • Leveraging API Gateway’s new developer portal features and comprehensive documentation capabilities enables systematic publication and management of agent AI system APIs for external developers.
  • Rocket Close’s case study demonstrates that security design combining row-level data permissions and audit trails can meet compliance requirements for agent AI systems handling sensitive business data.