Amazon Bedrock Reviews

Name: Amazon Bedrock
Brand: Amazon Web Services (AWS)
Rating: 4.1 (13 reviews)

4.1 out of 5

13 reviews
100% willing to recommend

What is Amazon Bedrock?

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.

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Amazon Bedrock is the #2 ranked solution in top AI Infrastructure solutions and #12 ranked solution in top Infrastructure as a Service Clouds. PeerSpot users give Amazon Bedrock an average rating of 8.2 out of 10. Amazon Bedrock is most commonly compared to Microsoft Azure: Amazon Bedrock vs Microsoft Azure. Amazon Bedrock is popular among the large enterprise segment, accounting for 74% of users researching this solution on PeerSpot. The top industry researching this solution are professionals from a manufacturing company, accounting for 14% of all views.

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Featured Amazon Bedrock reviews

RodrigoBassani

Diretor at Hat Thinking

I have to gain more maturity to provide some improvements to Amazon Bedrock. I have a lot to do with the environment they already provided. For example, they are able to connect to any LLM solution such as Llama, Meta, Gemini, or ChatGPT. It is open; you just choose your favorite LLM solution, and you can integrate it into Amazon Bedrock. We have a lot of possibilities to do this integration at this moment; we just need to work on it, create more maturity, and then we can provide some enhancements that we can see on the solution as a whole. For companies in general, the main pain point or main issue related to Amazon Bedrock is security because they are not confident that all information is hidden by this kind of architecture. They wonder if they are providing some company information that can run away, and I think that is the challenge we have now. We need to find ways to work on it and make our clients' data secure. They are looking for that to guarantee that this is a great solution for companies that is also secure.

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Charles Powell

Advisory Board Member at AllmaGen, Inc.

I am not going to speak to their roadmap. Amazon operates Bedrock as an ecosystem supporting third-party models. I am speculating here, but I am sure those third-party models will always be present. However, one must consider that Amazon native models could proliferate Bedrock in the future. We would welcome Amazon native models to Bedrock, since, if they are natively built by Amazon, they are tuned to SageMaker and other Amazon service layers. They have done this somewhat for generative AI, however, 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.

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Mehul Raj

Assistant Manager - Sales at Velocis Systems

I work with an AWS partner, and we offer cloud managed services to our clients as well as reselling services. I've worked with Amazon Bedrock to create solutions, including an image generation solution and a chatbot for an ERP application for schools The ability to make changes in the…

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PeerResearch reports based on Amazon Bedrock reviews

Type	Title	Date
Category	Infrastructure as a Service Clouds (IaaS)	Jul 4, 2025	Download
Product	Reviews, tips, and advice from real users	Jul 4, 2025	Download
Comparison	Amazon Bedrock vs Microsoft Azure	Jul 4, 2025	Download
Comparison	Amazon Bedrock vs Amazon AWS	Jul 4, 2025	Download
Comparison	Amazon Bedrock vs Akamai Connected Cloud (Linode)	Jul 4, 2025	Download

Title	Rating	Mindshare	Recommending
Microsoft Azure	4.2	17.3%	96%	316 interviews Add to research
Google Vertex AI	4.2	N/A	100%	11 interviews Add to research

Valuable Features

Amazon Bedrock offers robust security, flexibility, and diverse foundational models from multiple providers. Users appreciate easy customization, integration with services like S3 and Lambda, and serverless cost-efficiency. The platform simplifies applications using pre-trained models, enhancing operational efficiency. It supports quick development, team involvement, and tailored insights. Users value its scalability, no need for infrastructure management, and innovation in AI experimentation through fine-tuning and continual pre-training.

"The impact of Amazon Bedrock's sophisticated natural language processing on our company's ability to predict future outcomes is very interesting because, before we were using some Python codes, we created server instances to upload it, and we had some difficulty integrating it with the ecosystem because all the features we were creating were manually based."
"One of the best features of Amazon Bedrock is that it is easy to use, and users do not have to worry about the infrastructure."
"Amazon Bedrock offers an environment where we only pay for the model we use, and AWS handles the scaling."

Room for Improvement

Amazon Bedrock requires better documentation and integration, cost transparency, and UI improvements. Competitors offer more affordable pricing. There's a need for enhanced agentic AI applications and API integration. Marketplace availability is limited, and security concerns persist. Introducing prompt engineering and supporting more complex features can enhance development efficiency. Voice, image support, and offering multiple responses to queries would benefit users seeking creative flexibility. Native model integration and hyperscale optimization are also desired.

"For companies in general, the main pain point or main issue related to Amazon Bedrock is security because they are not confident that all information is hidden by this kind of architecture."
"For companies in general, the main pain point or main issue related to Amazon Bedrock is security because they are not confident that all information is hidden by this kind of architecture."
"Overall, I rate Amazon Bedrock a seven out of ten. It is slightly difficult to integrate with our product."

ROI

Amazon Bedrock offers a high return due to its cost-efficiency and pay-for-what-you-use model, enabling experimentation with foundation models at low cost. Usage reduces manual intervention in case processing, decreasing time and human resource needs. The savings from improved efficiency cover costs, offering similar functionality as individual models. One perspective noted initial charges before deployment, though generally users enjoy reduced expenses without seeing preliminary returns hinder implementation.

Pricing

Amazon Bedrock users find its pricing reasonable for foundational model experimentation compared to other managed services. Its competitive pricing and licensing are flexible, often based on a pay-as-you-go model. However, costs may rise with high processing demands or enterprise versions. Users mention unexpected charges and emphasize the importance of application design to control expenses, noting significant cost efficiency if usage is optimized. Despite some high costs, the pricing aligns with user expectations for features provided.

"One customer paid around $100 to $200 per month, which was significant given their overall infrastructure costs."
"The cost of using Amazon Bedrock is quite high, as I incurred unexpected charges amounting to $130 USD within two weeks without actually deploying the model."

Popular Use Cases

Amazon Bedrock supports various applications, such as vector embeddings for data stores, integrating AI features like large language models, and facilitating AI-driven analytics. Users employ Bedrock for tasks including data pipeline management, sentiment analysis, chatbots, report generation, and project management. It enables rapid prototyping and deployment of AI functionalities, from text and image creation to SQL query generation, and helps enhance business practices such as customer support analysis and invoice processing.

Service and Support

Amazon Bedrock's customer service and support is highly responsive and effective. AWS technical support is quick to address inquiries, even under basic plans. Clients appreciate interactions with AWS contacts for resolving minor issues. Users rate the service as high as ten out of ten, citing helpfulness, quality, and the ability to find information independently. While some find Text and Kendra limited, overall satisfaction is high, with excellent documentation and ease with AI integration.

Deployment

Amazon Bedrock's initial setup varies in complexity among users. Some found it confusing at first, especially navigating the AWS console, while others described it as easy and fast. Familiarity with AWS ecosystems makes it user-friendly, though some had challenges with unexpected charges or security concerns. Expertise in AWS and programming skills impact setup time and success. Most found it straightforward with clear documentation, but some noted time-consuming aspects like privacy policies.

Scalability

Amazon Bedrock demonstrates strong scalability with seamless integration across AWS services. Increasing data volume enhances scalability. However, challenges include constraints typical for large language models and account limitations. Users acknowledge its ability to automatically adjust, yet express concerns about hyperscale deployment requiring alternative strategies. While some users emphasize its capacity for global scaling, others rate scalability as high, noting the intrinsic AWS trustworthiness in handling scalability effectively.

Stability

Amazon Bedrock is described as reliable and stable with scalability managed effectively through AWS. Users report consistent performance with no significant delays, error-free API responses, and the capability to handle increasing workloads. Most users rate stability between eight and ten out of ten, reflecting high satisfaction. AWS Lambda, AWS Transcribe, and Polly contribute to scalability, supporting claims of hassle-free deployment and management with no major issues experienced over extended periods.

These insights are based on the in-depth reviews provided by peers to help you make a better buying decision.

Download our Amazon Bedrock Buyer's Guide for additional reliable information.

Review data by company size

By reviewers

By visitors reading reviews

Top industries

By visitors reading reviews

Manufacturing Company

14%

Computer Software Company

12%

Financial Services Firm

11%

University

Transportation Company

Retailer

Healthcare Company

Media Company

Comms Service Provider

Consumer Goods Company

Wholesaler/Distributor

Educational Organization

Outsourcing Company

Pharma/Biotech Company

Recreational Facilities/Services Company

Government

Legal Firm

Logistics Company

Insurance Company

Non Profit

Real Estate/Law Firm

Construction Company

Energy/Utilities Company

Performing Arts

Hospitality Company

Compare Amazon Bedrock with alternative products

Learn more about Amazon Bedrock

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?

Security: Provides robust measures to ensure data protection.
Model Flexibility: Allows customization of foundational models.
Serverless Architecture: Offers cost-efficient, scalable resources.
Provider Access: Connects with models from different vendors.

What benefits should be considered?

Model Modification: Enables quick adjustments to suit needs.
Development Speed: Facilitates fast application development.
AI Integration: Integrates seamlessly into existing offerings.

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.