Introducing Amazon Bedrock … What to know?

Emilio Taylor
5 min readMay 18, 2023

Demystifying Amazon Bedrock: Discover this powerful AI platform's capabilities and use cases for business success.

Photo by Christian Wiediger on Unsplash

Table of Contents

If you’re in the tech industry, you’ve likely heard of Amazon Web Services (AWS), Amazon’s cloud computing platform that provides businesses with various tools and services to help them build and scale their applications. One of the newer services that AWS has introduced is Amazon Bedrock, an AI platform designed to help businesses build, train, and deploy machine learning models. In this article, we’ll provide a for-dummies explanation of what Amazon Bedrock is, what it isn’t, everyday use cases, and a high-level use case with implementation steps and projected costs based on usage.

What is Amazon Bedrock?

Amazon Bedrock is an AI platform providing businesses with comprehensive tools and services to help them build, train, and deploy machine learning models. The platform is designed to be scalable, secure, and easy to use, even for those without extensive AI or machine learning experience.

At its core, Amazon Bedrock is a machine learning development platform that provides access to various tools and services, including pre-built algorithms, model training and deployment tools, and a comprehensive data management system. These tools allow businesses to build and deploy AI models quickly and efficiently without worrying about the underlying infrastructure.

What Amazon Bedrock isn’t

It’s important to note that Amazon Bedrock is only a turnkey solution for some AI problems. While it provides businesses with a range of powerful tools and services, it still needs to replace the need for human expertise. Companies still need experts who understand the underlying technology and can develop and refine the models as needed.

Additionally, Amazon Bedrock isn’t a standalone service. Bedrock works with other AWS services, such as Amazon S3 (Simple Storage Service) for data storage, AWS Lambda for serverless computing, and AWS SageMaker for machine learning model development. Businesses that are already using AWS will find Amazon Bedrock to be a valuable addition to their toolkit.

Everyday Use Cases for Amazon Bedrock

Amazon Bedrock is used to develop a wide range of AI applications, from predictive maintenance to natural language processing. Here are a few use cases:

  • Predictive Maintenance: Amazon Bedrock can be used to develop machine learning models to predict when equipment is likely to fail, allowing businesses to schedule maintenance before a breakdown occurs.
  • Fraud Detection: Amazon Bedrock can be used to develop models to detect fraud in financial transactions, helping companies to identify and prevent fraudulent activity.
  • Natural Language Processing: Amazon Bedrock can create models to analyze and interpret natural language, allowing businesses to automate customer service and support.
  • Image Recognition: Amazon Bedrock can be used to develop models to analyze and interpret images, allowing companies to automate tasks such as quality control in manufacturing.

Use Case Implementation & Projected Costs

Let’s walk through a sample cost breakdown based on a fraud detection use case based on an HR platform, absence management supporting 100,000 lives, supporting 15,000 claims per year, with an average of 10,000 drivers licenses to verify identity annually, 10,000 health provider paperwork to scan for physician approval annually to identify how many claims have invalid licenses submitted and how much provider paperwork is invalid signaling fraud. Note: These projected costs are for example purposes only. Please research specific costs accordingly.

Implementation Steps:

  1. Data Collection: Collect absence management data, driver’s license data, and health provider paperwork data. The absence management data will include details of 100,000 employees and their claims, while the driver’s license data and health provider paperwork data will be scanned annually.
  2. Data Cleaning: Clean the data and remove duplicates or irrelevant information to ensure high-quality data for model training.
  3. Data Labeling: Label the data for model training based on identifying invalid licenses and health provider paperwork signaling fraud.
  4. Model Training: Train a fraud detection model using Amazon Bedrock’s pre-built components for image classification and natural language processing.
  5. Model Testing and Validation: Test the model with a small data set and validate its accuracy before deploying it in a production environment.
  6. Model Deployment: Deploy the model to a cloud environment and create an API endpoint to receive claims data and detect fraud.
  7. Continuous Monitoring and Improvement: Continuously monitor the model’s performance and improve it based on feedback and new data.

Projected Costs:

  1. Data Storage: The estimated cost of data storage for absence management data, driver’s license data, and health provider paperwork data would be around $34 per month ($4 per month for absence management data, $10 per month for driver’s license data, and $20 per month for health provider paperwork data).
  2. Machine Learning Training: The cost of training the fraud detection model will depend on the complexity of the model and the amount of computing resources required. Assuming a medium-sized model, training costs can range from a few hundred dollars to a few thousand dollars.
  3. Model Deployment: Assuming an average of 15,000 claims per year, model deployment costs around $15 per month.
  4. Continuous Monitoring and Improvement: The cost of monitoring and improving the model would depend on the frequency of updates and the amount of data involved. Assuming monthly updates and a moderate amount of data, the cost would be around $50 per month.

Overall, the estimated cost for developing a fraud detection model using Amazon Bedrock for the provided use case would be around $400 — $2,500 per month, depending on the complexity of the model and the amount of data involved.

Signing Up for Amazon Bedrock

Conclusion

Amazon Bedrock is a powerful AI platform that provides businesses with various tools and services to help them build, train, and deploy machine learning models. With its scalable infrastructure, pre-built algorithms, and data management system, Amazon Bedrock makes it easy for businesses to develop AI applications, even if they need extensive AI or machine learning expertise.

While Amazon Bedrock isn’t a turnkey solution for all AI problems, Bedrock can develop a wide range of applications, from predictive maintenance to natural language processing. And with its low projected costs, businesses can get started with AI quickly and affordably, unlocking the potential benefits of this transformative technology.

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Emilio Taylor

Salesforce Practice Leader, Technology Enthusiast, Entrepreneur, Integrator, Architect, Developer, and Overall Cloud Advocate.