G2

Atharva P.

Cloud BI Engineer

Enterprise (> 1000 emp.)

7/24/2026

"Enterprise-Ready Generative AI with Multiple Foundation Models in One Managed Service"

4.5/5

What do you like best about AWS Bedrock?

What I like most about Amazon Bedrock is that it gives access to multiple leading foundation models through a single managed service, without the need to manage any underlying infrastructure. It enables organizations to build generative AI applications using models from Anthropic, Meta, Amazon, Mistral AI, Cohere, and Stability AI, while also integrating smoothly with existing AWS services.

Its serverless architecture, built-in security, and support for Retrieval-Augmented Generation (RAG), Knowledge Bases, and Agents make it a strong choice for enterprise AI applications. Review collected by and hosted on G2.com.

What do you dislike about AWS Bedrock?

Pricing can add up quickly for high-volume inference workloads, particularly when you’re using larger foundation models. Choosing the right model to balance latency, output quality, and cost often takes some trial and error, and a few of the more advanced customization options still feel more limited than what you can do with self-hosted open-source models. Review collected by and hosted on G2.com.

What problems is AWS Bedrock solving and how is that benefiting you?

Amazon Bedrock addresses the challenge of building enterprise generative AI applications without having to manage GPU infrastructure or handle individual model deployments.

Example:

We built an internal knowledge assistant using Amazon Bedrock Knowledge Bases connected to documents stored in Amazon S3. Employees could ask questions in natural language, and Bedrock would retrieve the most relevant documents, generate responses using Anthropic Claude, and enforce secure access controls through IAM.

Overall, this significantly improved knowledge discovery for our teams while removing the operational overhead of managing large language models. Review collected by and hosted on G2.com.