Amazon Bedrock Reviews

Name: Amazon Bedrock
Brand: Amazon Web Services (AWS)
Rating: 4.0 (15 reviews)

4.0 out of 5

15 reviews
93% 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 8.0 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 66% of users researching this solution on PeerSpot. The top industry researching this solution are professionals from a computer software company, accounting for 13% 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)	Aug 20, 2025	Download
Product	Reviews, tips, and advice from real users	Aug 20, 2025	Download
Comparison	Amazon Bedrock vs Microsoft Azure	Aug 20, 2025	Download
Comparison	Amazon Bedrock vs Amazon AWS	Aug 20, 2025	Download
Comparison	Amazon Bedrock vs Akamai Connected Cloud (Linode)	Aug 20, 2025	Download

Title	Rating	Mindshare	Recommending
Microsoft Azure	4.2	16.6%	96%	316 interviews Add to research
Google Vertex AI	4.2	N/A	100%	12 interviews Add to research

Valuable Features

Amazon Bedrock offers diverse model options, security features, and easy integration with company data. It allows customization via fine-tuning, supports serverless operations for efficiency, and provides flexibility in parameter adjustments. Users benefit from pre-trained models, scalable environments without infrastructure concerns, and seamless integration with services like Amazon S3 and AWS Lambda. Its design facilitates quick AI development, content creation, and operational cost savings.

"The most valuable features of Amazon Bedrock include scalability, ease of access, having 20 to 25 plus pre-trained models, and scaling capabilities."
"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."

Room for Improvement

Amazon Bedrock requires enhancements in documentation and cost transparency. Users desire better integration, a refined user interface, and support for voice and images. Complexity in Gen AI and API access could be elevated. Security confidence is crucial for companies. Optimization for hyperscale use and marketplace expansion is needed. Multiple responses to queries and prompt engineering methods would ease development, and dependency on technical resources is a concern.

"What could be improved for Amazon Bedrock to make it more mature is that AWS needs to consider bringing their platforms together, and not having different ML and AI platforms."
"The initial setup of Amazon Bedrock is somewhat complex as it requires integration with two to three services."
"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."

ROI

Amazon Bedrock delivers significant return on investment through cost-efficiency, using a pay-as-you-go model that promotes cost-effective experimentation with foundational models. It enables companies to cut manual intervention in case processing from 45% to 25%, reducing time and human resources. The platform offers time and resource savings by replicating the functionality of individual models cost-effectively. However, some users incur charges before deployment, hindering perceived benefits.

Pricing

Amazon Bedrock's pricing is generally seen as reasonable and competitive, particularly for users experimenting with foundation models. It utilizes a pay-as-you-go model, with costs linked to CPU cycles, memory, and the type of LLM model used. While the costs can be high for enterprise LLM solutions and unexpected charges have been noted, many find the pricing structure flexible and manageable within budget constraints. Pricing depends on application design, optimizing for utilization can reduce expenses.

"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 is primarily utilized for integrating AI into client offerings, facilitating vector embeddings for RAG applications, and acting as a bridge to foundational Gen AI models. Companies employ it for large language models, generating SQL queries, enhancing customer support, and automating processes like invoicing. Users leverage it for tasks from text summarization to creating customized chatbots, with capabilities to prototype enterprise use cases, utilizing models like Claude.

Service and Support

Amazon Bedrock's customer service and support are generally responsive and helpful, often solving issues swiftly without needing escalation. Users appreciate the direct communication and self-service options via the portal. Technical support earns an eight or nine out of ten, though improvements in certain areas are noted. Service quality depends on the representative, with some users building components independently due to the platform's novelty. AI integration and documentation significantly enhance user experience.

Deployment

Amazon Bedrock's initial setup varies in complexity, with some finding it straightforward due to familiarity with AWS, while others encounter challenges with integration, navigation, or security configurations. Setup time ranges from five minutes to several months depending on expertise. Consistent ecosystem benefits experienced users, but unexpected charges and skill deficiencies can complicate the process. Familiarity with Python aids in mitigating challenges related to data encryption, integrity topics, and creating roles and restrictions.

Scalability

Amazon Bedrock offers robust scaling features, trusted by many for its seamless integration with AWS services. Users highlight its capability to handle increased data volumes, yet note some inherent limitations such as rate per limits. There are varying sentiments on its ability to scale globally, with some expressing concerns over hyperscale challenges and account limitations. The reliance on AWS for automatic scaling is appreciated, though pricing with increased traffic is a consideration. Scalability ratings vary, generally leaning positive.

Stability

Amazon Bedrock is known for its reliability and stability, aligning with AWS's reputation. Users report consistent performance, handling both simple and complex tasks efficiently. No issues have been encountered over several months, and it's praised for managing workloads effectively. It integrates well with AWS Lambda, Transcribe, and Polly, demonstrating high scalability. Many rate its stability highly, highlighting its capability to return results without errors or timeouts. Users emphasize its reliable operation with no significant complaints.

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

Computer Software Company

13%

Manufacturing Company

12%

Financial Services Firm

University

Media Company

Transportation Company

Retailer

Outsourcing Company

Healthcare Company

Comms Service Provider

Government

Educational Organization

Consumer Goods Company

Recreational Facilities/Services Company

Pharma/Biotech Company

Real Estate/Law Firm

Wholesaler/Distributor

Insurance Company

Non Profit

Hospitality Company

Construction Company

Performing Arts

Logistics Company

Legal Firm

Energy/Utilities Company

Recruiting/Hr Firm

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.