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 68% of users researching this solution on PeerSpot. The top industry researching this solution are professionals from a manufacturing 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)	Jul 14, 2025	Download
Product	Reviews, tips, and advice from real users	Jul 14, 2025	Download
Comparison	Amazon Bedrock vs Microsoft Azure	Jul 14, 2025	Download
Comparison	Amazon Bedrock vs Amazon AWS	Jul 14, 2025	Download
Comparison	Amazon Bedrock vs Akamai Connected Cloud (Linode)	Jul 14, 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%	12 interviews Add to research

Valuable Features

Amazon Bedrock offers security, flexibility, and cost efficiency. Users appreciate its ease of use, integration with pre-trained models, and customization options. It supports diverse foundational models and simplifies data storage and processing. Bedrock's serverless nature and model parameter adjustments enhance user trust and efficiency. It allows uploading call analyses for improved operations and helps create intelligent agents without extensive coding. Integration with services like S3 and Lambda automates analysis tasks.

"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 enhanced documentation, smoother integration, and cost transparency. There is a need for a more intuitive user interface and better support for scalable use. Improvements could include more integration options and additional AI capabilities. Users express concern about security and seek clarity on pricing and features. The focus should also be on providing prompt engineering methods and increasing the platform’s complexity to align with open-source frameworks.

"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 provides substantial ROI through cost-efficiency and a pay-for-what-you-use approach, allowing experimentation with foundation models at a low price. It reduces manual intervention in case processing, decreasing time and human resources, with savings covering its cost. Users report time and resource benefits, offering similar functionality as individual models. However, some experienced charges before model deployment, affecting perceived advantages.

Pricing

Enterprise users report Amazon Bedrock's pricing and licensing as flexible and generally reasonable, especially for experimental use of foundation models. While some find costs high, particularly for enterprise LLM versions and data processing, others note the cost efficiency due to its consumption-based model. Pricing depends on model versions and usage, with savings possible through efficient application design that minimizes reliance on Bedrock's processing power. Competitive compared to providers like Azure, fees are justified by Bedrock's features.

"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's primary use cases include vector embeddings for data storage in RAG applications, serving as a bridge between applications and Gen AI models, integrating AI into client offerings, creating and deploying large language models, generating AI-driven content, and enhancing enterprise processes. Organizations leverage it for creating knowledge bases, generating SQL queries, developing chatbots and image generators, performing sentiment analysis, processing customer support calls, analyzing invoices, and extracting data from PDFs using OCR capabilities.

Service and Support

Amazon Bedrock's customer service and support are often described as efficient and quick to respond, earning high praise and ratings. Users find technical support helpful, particularly when dealing with AWS ecosystem-related questions. Some mention the importance of independent problem-solving using the ample information on the portal. The service is generally rated highly, with AI integration enhancing efficiency. A few suggest improvements for Text and Kendra features while others find no need for escalation to support services.

Deployment

Users found Amazon Bedrock's initial setup to be generally manageable, especially when familiar with the AWS ecosystem, yet some faced complexities. Many noted that it became routine over time. Familiarity with AWS tools was advantageous, although some experienced confusion in the AWS console. While a few rated the experience positively with quick completion, others mentioned challenges related to team expertise and privacy policies. Unexpected charges and skill set deficiencies posed potential hurdles.

Scalability

Amazon Bedrock is generally scalable, with automated scaling handled by AWS. Users experience benefits from easy integration with AWS services. Some concerns exist about limitations like rate limits and potential challenges at hyperscale, but overall, it receives positive assessments for scaling efficiently with data volume and integrating AWS services. While trusted for scaling, a few note potential improvements regarding account limitations. Suitable for varying scales, some rate its scalability highly.

Stability

Amazon Bedrock is praised for its reliability and stability, consistent with AWS's reputation. Users report effective management of scalability and security, with stable performance across tasks. Over several months, stability remains high, handling workloads effectively with strong scalability. It's rated highly, often a nine or ten out of ten, for stable operations without errors or timeouts. Customers have not experienced issues, reflecting consistent satisfaction with Amazon Bedrock's robust performance.

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

13%

Computer Software Company

12%

University

10%

Financial Services Firm

10%

Transportation Company

Retailer

Outsourcing Company

Media Company

Healthcare Company

Comms Service Provider

Consumer Goods Company

Educational Organization

Recreational Facilities/Services Company

Non Profit

Wholesaler/Distributor

Insurance Company

Government

Pharma/Biotech Company

Logistics Company

Real Estate/Law Firm

Hospitality Company

Construction Company

Legal Firm

Recruiting/Hr Firm

Energy/Utilities Company

Performing Arts

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.