SAP S4HANA on AWS and Amazon Bedrock are competitors in cloud-based enterprise solutions. SAP S4HANA on AWS seems to have the upper hand with its comprehensive ERP functionalities, while Amazon Bedrock excels in AI capabilities and flexible model integration, appealing to AI-driven enterprises.
Features: SAP S4HANA on AWS offers comprehensive modules covering finance, manufacturing, and analytics, allowing effective management of complex ERP functions. Its seamless integration with AWS infrastructure reduces hardware dependency, enhancing cost-efficiency. Amazon Bedrock provides customizable AI models and easy experimentation with Generative AI, making it ideal for companies seeking AI-driven insights. The integration with pre-trained models is a significant advantage for businesses focused on AI applications.
Room for Improvement: SAP S4HANA on AWS needs a simplified interface and improved licensing model. Users have raised concerns about technical support, hardware costs, and integrating with newer technologies. There's also a call for more data centers and enhanced training resources. For Amazon Bedrock, improving cost transparency and expanding AI capabilities are key areas. Better documentation and additional integration points would refine user experience, alongside addressing unexpected costs.
Ease of Deployment and Customer Service: SAP S4HANA on AWS offers flexibility with public, private, and hybrid cloud deployment options, though its technical support needs improvement due to reported response delays. Amazon Bedrock focuses on public cloud deployment, known for straightforward implementation and generally positive technical support with efficient response times, yet a more extensive knowledge base could benefit the growing community.
Pricing and ROI: SAP S4HANA on AWS is viewed as costly due to high hardware expenses and complex licensing, but it yields a strong return on investment with increased efficiency over time. Amazon Bedrock is competitively priced for its features, though concerns about unexpected charges persist. Its cost model is appealing for AI experimentation compared to other offerings, with users noting its fair pricing for available capabilities.
On a very good implementation, usually, if the scale of the business is large, the implementation can give a payback within six, seven, or eight months of implementation.
Although our investment was higher compared to the previous ERP system, we are able to derive ROI from SAP S4HANA on AWS.
So, you always have to bridge the gap by presenting scenarios, getting recommendations, and testing or validating those assumptions.
They have a support model available, with first-level support handling initial issues when I integrate the system.
We received the right support during our implementation and continue to benefit from it.
Amazon Bedrock is quite highly scalable, but there are some limitations they impose on the accounts, which could be an area for improvement.
It scales well with AWS Lambda, AWS Transcribe, and Polly.
It is scalable on a truly global basis.
AWS has been running probably 96% of Fortune 500 companies across the globe, so scalability is not an issue.
The product is versatile and can manage complexity beyond expectations.
As a finance controller, we have seen improvements in finance deliverables, SLAs in payables, and reconciliation timelines.
In AgenTek AI business, the only foundation models we can rely on for scaling now are the Cloud 3.5 models like Haiku and SONNET, designed for low latency and complex AI business use cases.
If AWS provided methods, like five or six prompts that yield specific results, it would ease development.
The user interface of Amazon Bedrock on the management console needs improvements.
The interface and interaction with the technical team require intensive training.
SAP introduced flexible workflows, which are even better if I want customized workflows for my documentation within the procurement domain.
Having these integrations as a single source rather than working in silos would be beneficial for customers.
Our cost is incredibly low, operating for a few hundred dollars a month in production.
One customer paid around $100 to $200 per month, which was significant given their overall infrastructure costs.
The pricing and licensing of Amazon Bedrock are quite flexible.
SAP is not cheap, with many hidden costs encountered during implementation.
The initial setup required a higher investment, but the return on investment has justified the cost.
It has improved operational costs and efficiency significantly, saving money and enhancing the quality of operations.
Amazon Bedrock offers an environment where we only pay for the model we use, and AWS handles the scaling.
The ability to make changes in the foundational model is valuable since different customers have specific needs, allowing customization.
The costing and personnel planning integration are among the strongest areas of this solution.
From the finance side, we have enhanced our internal controls and reduced the timeline for closing the month from a year to just two days.
It manages complexity in various industries such as banking, manufacturing, and trading.
Amazon Bedrock enhances AI integration by providing a suite of foundational models with customization options. It simplifies data integration and offers security, traceability, and cost-efficiency through its serverless architecture.
Amazon Bedrock empowers users by offering models from multiple providers, ensuring model flexibility and ease of use. It supports quick development for applications such as vector search and SQL query generation. While the system is beneficial for AI integration and analytics enhancement, there is a desire for improved documentation, smoother integration, and more competitive pricing. Additional integration points, markdown features, and support for voice and images could enhance its use. Users also seek to optimize for hyperscale use and receive multiple responses for creative tasks.
What are the key features of Amazon Bedrock?
What benefits should be considered?
In industries like data analytics and software development, Amazon Bedrock is implemented for tasks such as deploying large language models, performing sentiment analysis, and creating chatbots. It's used for generating AI-driven text and images, and enhancing data retrieval via SQL query generation.
SAP customers of all sizes can fully realize all the benefits of the SAP S/4HANA, on-premise edition on the AWS Cloud. With SAP S/4HANA, on-premise edition on the AWS Cloud you can:
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