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    GenAI Implementation & AWS Bedrock Consulting Services

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    Sold by: Rambunct 
    Transform your business with enterprise-grade Generative AI solutions built on AWS Bedrock. Our expert consulting team accelerates your AI journey from strategy to production deployment, delivering custom GenAI applications with robust security, cost optimization, and responsible AI practices tailored to your organizational needs.

    Overview

    Accelerate your organization's AI transformation with our comprehensive AWS Generative AI consulting service. We combine deep artificial intelligence expertise with proven enterprise implementation methodologies to deliver production-ready GenAI solutions that drive measurable business outcomes.

    Our experienced team guides you through every phase of your AI journey, from initial use case identification and foundation model selection to production deployment and ongoing optimization. We specialize in leveraging Amazon Bedrock, SageMaker, and the full AWS AI ecosystem to build scalable, secure, and cost-effective solutions tailored to your specific business requirements.

    We implement enterprise-grade GenAI capabilities including semantic search, conversational AI interfaces, intelligent content generation, and automated document processing. Our approach ensures proper data privacy controls, security governance, and compliance with industry regulations while maintaining operational excellence. We deliver robust architectures with integrated vector databases, optimized prompt engineering, RAG implementation, and comprehensive monitoring frameworks that enable sustainable AI operations at scale.

    Highlights

    • End-to-End GenAI Implementation: From strategy development through production deployment, we deliver complete AWS Bedrock solutions with foundation model selection, prompt optimization, RAG architecture, and enterprise security controls that accelerate time-to-value for your AI initiatives.
    • Enterprise-Grade Security & Compliance: Our implementations include comprehensive data privacy controls, governance frameworks, and industry compliance measures while leveraging AWS native security services to ensure your GenAI applications meet organizational and regulatory requirements.
    • Production-Ready AI Operations: We establish robust monitoring, evaluation frameworks, and cost governance systems with automated scaling, performance optimization, and responsible AI practices that ensure sustainable, high-performing GenAI applications in production environments.

    Details

    Delivery method

    Deployed on AWS

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    Pricing

    Custom pricing options

    Pricing is based on your specific requirements and eligibility. To get a custom quote for your needs, request a private offer.

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    Support

    Vendor support

    Our dedicated GenAI support team provides comprehensive assistance for all AWS Bedrock implementation and AI application management services. We offer multiple support channels including email support, phone consultation, and emergency escalation procedures for critical AI production issues.

    Support Services Include:

    GenAI architectural guidance and AWS Bedrock best practice recommendations AI model troubleshooting assistance and prompt optimization support Performance tuning for RAG implementations and vector database operations Access to our GenAI knowledge base and implementation documentation portal Regular AI application health checks and proactive monitoring alerts Foundation model selection guidance and fine-tuning recommendations

    Contact Methods:

    Email: support@rambunct.com  Phone: Available during business hours with emergency escalation for production AI systems Support Portal: 24/7 access to GenAI documentation, best practices, and ticket management

    Response Times:

    Standard Support: 4-hour response during business hours for general GenAI inquiries Priority Issues: 1-hour response for AI application performance issues with escalation procedures Emergency Support: Immediate response for production-critical GenAI system failures