As an Advanced Tier AWS Consulting Partner, zeb is excited to present our Generative AI Model Acceleration Program on the AWS Marketplace. This engagement is designed to empower organizations to rapidly develop and deploy custom generative AI models that are aligned with their unique business goals and research objectives. By leveraging the power of Amazon SageMaker, Amazon Bedrock, and state-of-the-art Trainium instances, we provide a streamlined and efficient pathway to harness the capabilities of generative AI.

Our process begins with a thorough assessment of your specific needs and objectives, allowing us to tailor the development of your generative AI models for maximum impact.

Key Features

Custom model development: Building generative AI models from scratch that are precisely aligned with your business or research needs by leveraging Amazon SageMaker.

Foundation Model Fine-Tuning: Utilizing Amazon Bedrock to fine-tune foundational models and perform continuous pretraining where applicable.

Best practices for LLM training: Employing proven strategies for training large language models from scratch on Amazon SageMaker or fine-tuning existing models on Amazon Bedrock, ensuring efficiency and optimal performance.

Comprehensive infrastructure setup: Crafting a customized architecture that leverages AWS services for seamless model development, training, and deployment.

Efficient model training: Utilizing AWS Trainium instances for cost-effective and high-performance training of large-scale generative AI models.

Integration and deployment support: Ensuring smooth integration of your custom models into existing systems and guiding you through deployment for immediate impact.

Ongoing support and optimization: Providing continuous assistance to refine and enhance your models, ensuring they evolve with your business and the latest AI advancements. (Optionally)

Our offering is more than just a technical solution; it's a partnership aimed at fostering innovation and driving business growth through the strategic application of generative AI. We are committed to working closely with you to unlock the full potential of AI and achieve transformative results.

Deliverables

Custom Model Development: Collaborate with our AI/ML experts to design and develop a generative AI model from scratch, tailored to your specific use case, and trained on your data.

Foundation Model Fine-Tuning: Collaborate with our AI/ML experts to fine tune existing foundation models and perform continuous pretraining using Amazon Bedrock.

Best Practices for LLM Training: Implement best practices for training large language models on Amazon SageMaker or fine-tuning existing models on Amazon Bedrock, ensuring efficient use of resources and optimal model performance.

Future-state Architecture Diagram: A future-state architecture diagram outlines the planned technological framework and components (AWS) envisioned for implementation.

Estimating Total Cost of Ownership (TCO): Utilize our pre-configured AWS Pricing Calculator for precise projection of operational expenses linked with the proposed solution on AWS.

Model Training and Optimization: Utilize AWS Trainium instances for efficient and cost-effective training of your large-scale generative AI models.

Integration and Deployment Support: Ensure seamless integration of your custom model into existing systems and workflows, with guidance on deployment strategies for optimal performance.

Ongoing Support and Optimization: Benefit from continuous support to refine and enhance your model, ensuring it evolves with your business or research needs.

Timeline

The assess and road mapping phase typically spans approximately 2 weeks, the implementation activities may require 8-12 weeks (depending on the scope, size of product and availability of your project sponsor and technical teams).

Next Steps

Our typical next steps involve showcasing our previously implemented solutions, submitting a proposal for implementation services, including future-state architecture recommendations, technical design and implementation, testing, and production cut-over.