Try our new research platform with insights from 80,000+ expert users
Amazon Bedrock Logo

Amazon Bedrock Reviews

Vendor: Amazon Web Services (AWS)
4.0 out of 5
Badge Leader
Leave a review

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.

Get the Amazon Bedrock Buyer's Guide and find out what your peers are saying about Amazon Bedrock, Microsoft Azure, Google Vertex AI and more!
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.
Buyer's Guide
Amazon Bedrock
August 2025
Get the report
Helped 866,685 peers since 2012

Featured Amazon Bedrock reviews

Read more reviews

PeerResearch reports based on Amazon Bedrock reviews

TypeTitleDate
CategoryInfrastructure as a Service Clouds (IaaS)Sep 5, 2025Download
ProductReviews, tips, and advice from real usersSep 5, 2025Download
ComparisonAmazon Bedrock vs Microsoft AzureSep 5, 2025Download
ComparisonAmazon Bedrock vs Amazon AWSSep 5, 2025Download
ComparisonAmazon Bedrock vs Akamai Connected Cloud (Linode)Sep 5, 2025Download
Suggested products
TitleRatingMindshareRecommending
Microsoft Azure4.215.5%95%321 interviewsAdd to research
Google Vertex AI4.2N/A100%12 interviewsAdd to research
 
 
Key learnings from peers

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
Company SizeCount
Small Business7
Midsize Enterprise1
Large Enterprise5
By reviewers
By visitors reading reviews
Company SizeCount
Small Business43
Midsize Enterprise13
Large Enterprise109
By visitors reading reviews

Top industries

By visitors reading reviews
Computer Software Company
13%
Manufacturing Company
12%
Financial Services Firm
10%
University
8%
Media Company
6%
Outsourcing Company
5%
Transportation Company
5%
Retailer
5%
Healthcare Company
4%
Comms Service Provider
4%
Construction Company
2%
Educational Organization
2%
Real Estate/Law Firm
2%
Recreational Facilities/Services Company
2%
Consumer Goods Company
2%
Government
2%
Wholesaler/Distributor
2%
Logistics Company
2%
Insurance Company
2%
Non Profit
2%
Hospitality Company
2%
Pharma/Biotech Company
2%
Performing Arts
1%
Legal Firm
1%
Energy/Utilities Company
1%
Recruiting/Hr Firm
1%

Compare Amazon Bedrock with alternative products

Go!

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.

Related questions

  • 25
When evaluating Infrastructure as a Service (IaaS), what aspect do you think is the most important to look for?
  • 24
Which Commercial and Open Source Software Do You Recommend for Private Clouds?
  • 40
Gartner's Magic Quadrant for IaaS maintains Amazon Web Service at the top of the Leaders quadrant. Do you agree?
  • 23
Pros/cons of Rackspace vs. other leading vendors?
  • 182
Which virtualization platform would you recommend to a healthcare company with 1000-5000 employees?
  • 2
Are there any reasons to opt for Rackspace vs. its cloud competitors?
  • 7
IaaS Solutions: Which did you choose, and What problem(s) has the solution solved for you?
  • 28
What is the difference between IaaS, SaaS, and PaaS?
  • 9
Which cloud IaaS/PaaS platform would you recommend learning to a newbie?
  • 30
Rackspace, Dimension Data, and others that were in last year's Challenger quadrant became Niche Players: Agree/ Disagree

Product Categories

Product Categories
Infrastructure as a Service Clouds (IaaS)
AI Infrastructure

Popular Comparisons

Popular Comparisons
Microsoft Azure vs Amazon Bedrock Logo
Microsoft Azure vs Amazon Bedrock
Google Vertex AI vs Amazon Bedrock Logo
Google Vertex AI vs Amazon Bedrock
Google Cloud vs Amazon Bedrock Logo
Google Cloud vs Amazon Bedrock
Oracle Cloud Infrastructure (OCI) vs Amazon Bedrock Logo
Oracle Cloud Infrastructure (OCI) vs Amazon Bedrock
Alibaba Cloud vs Amazon Bedrock Logo
Alibaba Cloud vs Amazon Bedrock
Google Firebase vs Amazon Bedrock Logo
Google Firebase vs Amazon Bedrock
NVIDIA DGX Cloud vs Amazon Bedrock Logo
NVIDIA DGX Cloud vs Amazon Bedrock
GroqCloud Platform vs Amazon Bedrock Logo
GroqCloud Platform vs Amazon Bedrock
Modal Labs vs Amazon Bedrock Logo
Modal Labs vs Amazon Bedrock
Baseten vs Amazon Bedrock Logo
Baseten vs Amazon Bedrock
See all alternatives
 
Amazon Bedrock Reviews Summary
Author infoRatingReview Summary
Diretor at Hat Thinking4.0Amazon Bedrock simplifies processing incoming invoices for a logistics company by easily integrating various LLMs without infrastructure concerns. While the platform accelerates architecture creation, security remains a primary concern, requiring enhancements to ensure data protection for company information.
Advisory Board Member at AllmaGen, Inc.4.5We use Amazon Bedrock to enhance our business processes, offering robust AI model deployment and secure data handling. While Bedrock supports third-party models, we hope for more Amazon native models that integrate seamlessly with SageMaker for improved performance.
Cloud Architect at Acmegrade4.0I used Amazon Bedrock to build a customized AI for my wine website; its scalability, model variety, and knowledge base integration were valuable, though setup was complex and pricing could improve. Overall, it met my specific business needs.
Senior Software Developer at a tech vendor with 10,001+ employees3.5We use Amazon Bedrock on AWS for generative AI tasks, leveraging Anthropic Claude LLM to answer user questions efficiently. It's beneficial that we only pay for the model used, but AWS lacks prompt engineering methods, which would simplify development.
Assistant Manager - Sales at Velocis Systems5.0I've used Amazon Bedrock to develop solutions like an image generator and a chatbot for school ERP systems. Its customizable foundational model and no-code features are valuable, though the management console's user interface could use some improvement.
Data Lake and MLOps Lead at a energy/utilities company with 10,001+ employees3.0I’ve used Amazon Bedrock for 18 months and find its LLM capabilities valuable, but integration is complex, scalability is challenging, and support is inconsistent; overall, I rate it 6 out of 10 for maturity and usability.
Data Scientist at a marketing services firm with 1-10 employees4.0I primarily use Amazon Bedrock for creating and deploying language models, benefiting from its model variety and knowledge base integration. Although it could improve API integrations, it's cost-effective, saving time and resources compared to alternatives like Gemini and Llama.
Solutions Architect & PMO at AS TV Play Baltics/TV3 Group4.0I use Amazon Bedrock primarily for analyzing customer support calls. Its AI engine provides summaries and evaluations of agents, improving operational costs and efficiency. I haven't noticed any areas needing improvement, and I deploy it on AWS.