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    Agentic workflows with DeepSeek & Open-Source Reasoning models on AWS

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    Sold by: XenonStack 
    Agentic RAG powered by the multi-Agent framework helps enterprises implement intelligent, conversational support systems using open-source foundation models and AWS-native services. It utilizes a sophisticated multi-agent Retrieval Augmented Generation (RAG) architecture with Llama 3.3 and DeepSeek-R1 LLMs, providing a flexible, scalable, and cost-efficient alternative to proprietary customer support AI systems. The architecture is centred around a three-tier agent system: Orchestration Agents (Llama 3.3), Knowledge Base Agents (DeepSeek-R1), and Response Generation Agents (Llama 3.3), which collaborate to process customer inquiries, retrieve contextual information, and generate personalized responses.

    Overview

    Overview

    Xenonstack's Agentic RAG solution transforms operations through an advanced multi-agent system powered by open-source AI models on AWS. Our solution combines DeepSeek-R1's sophisticated reasoning capabilities with Llama 3.3's versatility to create a comprehensive support ecosystem that dramatically reduces response times, automates resolution, processes documents intelligently, and delivers consistent, high-quality customer experiences at scale.

    Product Benefits

    1. Improved Customer Experience
    2. Increased Efficiency
    3. Scalability
    4. Cost-Effective
    5. Security & Compliance

    Key Components

    1.Orchestration Agent (Llama 3.3) 2. Knowledge Base Agent (DeepSeek-R1) 3. Response Generation Agent (Llama 3.3) 4. Document Processing Pipeline 5. Vector Store 6. Channel Integration

    Use Cases

    Primary Use Cases:

    1.Automated customer support through WhatsApp

    1. Intelligent processing of customer-uploaded documents and files

    2. Complex query resolution with multi-step reasoning

    3. Knowledge extraction and utilization from enterprise document repositories

    4. Contextual, personalized customer conversations with memory

    Customer Pain Points Addressed:

    1. Reducing response time from hours to seconds

    2. Eliminating repetitive tasks for human agents

    3. Ensuring consistent, accurate responses

    4. Processing and understanding uploaded documents

    5. Maintaining conversation context across interactions

    Industry-Specific Applications:

    1. Financial Services

    2. Healthcare

    3. Retail & E-commerce

    4. Telecommunications

    5. Insurance

    Highlights

    • Xenonstack provides enterprise-grade agentic workflows on AWS to build intelligent, context-aware support experiences using DeepSeek, Llama, and advanced RAG architecture with flexible channel integration.
    • We help organizations automate support operations with reasoning agents that handle inquiries, process documents, and maintain contextual conversations.
    • Our multi-agent system—leveraging Llama for orchestration and DeepSeek-R1 for reasoning—delivers faster, more accurate responses than single-model solutions.

    Details

    Sold by
    XenonStack 
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    Implementation 
    Managed Services 
    Delivery method
    Deployed on AWS

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