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    Agent Search

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    Sold by: XenonStack 
    AgentSearch is a powerful semantic search platform that integrates structured, semi-structured, and unstructured enterprise data. Powered by a graph-enhanced RAG architecture and Amazon Bedrock, it provides fast, explainable, and secure AI-driven search responses. The platform is optimized for scalability and performance, leveraging Kubernetes for parallel indexing and built-in security features like AWS IAM and VPC. It’s ideal for use cases in enterprise knowledge discovery, legal compliance, policy Q&A, and e-commerce insights. Designed for teams in regulated industries, AgentSearch improves productivity, reduces research time, and ensures compliance through auditable AI-driven search.

    Overview

    Key Features:

    • AgentSearch offers unified semantic search capabilities across structured, semi-structured, and unstructured enterprise data.
    • Its graph-enhanced RAG architecture powered by Bedrock ensures accurate, explainable responses by combining language models with graph context.
    • The platform enables fast and parallel indexing of large datasets using Kubernetes workers, which significantly reduces processing time.
    • Security and auditing are built-in, leveraging AWS IAM for access control, VPC for network isolation, and CloudWatch for monitoring.
    • Additionally, AgentSearch includes observability and automatic performance scaling features through Kubernetes and Horizontal Pod Autoscaler (HPA).

    Use Cases:

    • AgentSearch supports a wide range of enterprise applications.
    • It powers Enterprise Knowledge Discovery, enabling employees to extract relevant information quickly across departments.
    • In the Legal and Compliance domain, it facilitates deep search across regulatory and policy documents. It is ideal for Policy and Risk Q&A in highly regulated sectors like BFSI and Healthcare, helping teams make informed decisions. In E-commerce, it enhances catalog intelligence, allowing businesses to gain richer insights from product data.

    Target Users:

    • AgentSearch is designed for a range of enterprise users.
    • Business Analysts can use it to extract strategic insights quickly.
    • Legal and Compliance Teams benefit from its precise document discovery capabilities.
    • Data Engineers can leverage the platform for building robust data search pipelines.
    • Knowledge Workers in regulated industries such as finance and healthcare can rely on it for fast, explainable, and secure information retrieval.

    Technical Requirements:

    • To deploy AgentSearch, organizations need an AWS Account with Amazon EKS, IAM, and VPC properly configured. Enterprise data should be available across Amazon S3, Neptune, RDS, and OpenSearch. Additionally, access to Amazon Bedrock APIs is necessary to power the generative AI layer.
    • Operational knowledge of Kubernetes is also required for managing the microservice-based architecture and deployment.

    Technical Requirements:

    • To deploy AgentSearch, organizations need an AWS Account with Amazon EKS, IAM, and VPC properly configured. Enterprise data should be available across Amazon S3, Neptune, RDS, and OpenSearch.
    • Additionally, access to Amazon Bedrock APIs is necessary to power the generative AI layer.
    • Operational knowledge of Kubernetes is also required for managing the microservice-based architecture and deployment.

    Deployment Architecture:

    • The solution is deployed using a microservice architecture on Amazon EKS.
    • It includes a GraphRAG API server alongside indexing workers that process and serve data efficiently.
    • Secure access to data sources such as S3, RDS, Neptune, and OpenSearch is enforced using AWS IAM.
    • All data transfers are encrypted via TLS, and data at rest is secured using SSE-S3 encryption. Observability is handled via Amazon CloudWatch, while APIs are exposed through API Gateway and Ingress controllers for managed access.

    Benefits:

    • AgentSearch delivers graph-aware, explainable AI responses across data silos, helping organizations improve search reliability.
    • It significantly reduces research time, thereby enhancing the productivity of teams across functions.
    • The platform enables traceable and auditable AI-driven search, a critical requirement for compliance in regulated sectors.
    • It is also designed with scalability, performance, and security in mind, making it suitable for large-scale enterprise deployments.

    Highlights

    • Modular agentic framework enabling intelligent task automation across workflows.
    • Seamless integration with leading LLMs for context-aware reasoning and responses.
    • Enterprise-grade scalability with built-in privacy, observability, and secure deployment.

    Details

    Sold by
    XenonStack 
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    Managed Services 
    Implementation 
    Delivery method
    Deployed on AWS

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