Amazon Q Reviews

I have been working with Amazon Q for three years. In Amazon Q, I work with what we call the client's CMS, Client Management System, whereby we input information from clients and process this information to have tracking dates of when items were created and their types. I work in the financial world dealing with hedge funds. We process new accounts, purchase subscription items, and redemption items. We obtain particular information concerning how it is being processed from the information we receive. It entails information that deals with trade types and the amount which investors would invest. It deals with account names or account numbers where we input this information online so that in the future someone can easily track this information using the tracking source key number and get the particular information needed.

I can tell you about a situation where we had new investors using Amazon Q. We were able to create new accounts for each of them with items appended and uploaded into their various systems. With this, we had tasks where we could monitor each investor with each document appended on the queue for easy reference rather than going back to our share folder or SharePoint to get various documents individually. We were able to go individually to various documents and check for each investor. The action we get is that we process these investors promptly because of the appended documents. It is easier to trace the amount, date, and type of investor investing in the company. We ensure that we get the right document for the right investor. The result is we avoid escalations and issues where different investors are processed incorrectly. We can analyze and pinpoint which document belongs to each investor and process the trade accordingly, reducing stress by approximately 99%.

Prio in Amazon Q is an application where we process client information. We go into this particular section to process and create new accounts. We input client information including contact information, email address, phone number, and residential address. We also process trades based on what investors want, whether subscription documents or redemptions. It helps us monitor the amount of trades booked and pending at month-end. It also helps generate statements to track how much investors have invested or remain with the company. The platform helps us track various funds in which different investors have invested.

What I appreciate about Amazon Q is the prompt information received when using the source key. It is easier to navigate through and track the amount of trades booked in a month or particular period. If an item is not completed, one can always return to complete it. Whether it has been moved to the QC side for second checking or remains in the processing queue, users can analyze it, make corrections, and fix it before sending to the final archive position.

The annotation feature in Amazon Q is particularly valuable. The annotation section deals with inputting information of what has been processed and helps checkers understand what processors have done. With the annotation part, users can trace and check if particular trades or information have been processed correctly. If there are missing items or documents, the annotation part reminds second checkers that specific information is missing, allowing processors to request particular documents before appending them to the queue. The ability to track and trace data needed for future reference ensures that information can be retrieved quickly.

What I would suggest for improvement in Amazon Q relates to feedback handling once processes are concluded. While the automation and information input capabilities are excellent, there should be better mechanisms for making changes after archival. Currently, if an item has been archived and requires changes for audit purposes, retrieving it requires creating a new item and linking it to the previous one. If archived processes could be retrieved with manager approval, it would help make corrections without creating multiple source keys. This would reduce queue workload and make processing time faster and more efficient.

Three years.

There were no other options. I chose this solution because it helps complete tasks efficiently.

I worked with the IT team to set up Amazon Q via MS Teams calls with screen sharing. We input the information together, and I received access about a week before starting use. The setup was straightforward, requiring only learning the features and understanding how to process items.

It was provided by the company.

Amazon Q has been very helpful in improving efficiency. When I started with the company, processing an item would take 30-40 minutes. Now, within 10 minutes, tasks are completed. It has made the job easier and faster.

For those considering Amazon Q, I recommend always learning and upgrading with it. It makes the job easier and faster, helps monitor queues, and provides reference points for future processes. It is really worth implementing and can help motivate employees. This solution deserves a rating of 9 out of 10.

I work with my company's technology team, who handle interactions with the Amazon team. When information, upgrades, or queries are needed, I communicate through my company's tech team to get tasks completed.

Regarding pricing and additional features, I am not part of the pricing team and cannot provide specific details, but research into these aspects could be beneficial for potential users.

I use it for personal tasks and work. For personal projects, when I'm working on a weekend hobby, I can use it to create APIs, which helps to bootstrap. If I have a data set which I want to analyze, I give it some prompts, and it's able to analyze.

Regarding work, I'm able to use it to correct my code. In regards to security compliance, I ensure I follow the best practices.

Most of the time I use it for technical tasks in regards to programming. It's able to actually understand human language regarding the context. For instance, I have an existing folder. I can give it a prompt for it to scan through and generate whether it's following the best practices, or if the code is not following the formatting and linting requirements. Additionally, if there's data I want to analyze, it's able to understand the natural language from the human perspective.

I use Amazon for cloud service operations, which is why I opt for Amazon Q.

Amazon Q is a valuable tool to boost productivity and helps deliver quality and value to customers.

Amazon Q is able to understand human language regarding the context and scan through folders to ensure best practices are followed. This ability to interpret natural language from a human perspective is quite valuable. Amazon Q helps boost productivity, enabling the delivery of quality and value to customers. Its capabilities in correcting code and analyzing data are commendable.

I currently use the free tier, and in all my use cases, it's been able to deliver. Even though machine learning models have errors, regarding its benchmark, it's able to perform well. The paid version would likely do more compared to the free version.

Sometimes feedback is needed immediately. It takes a bit of time because there is a workload. You'll get your feedback and a listening ear, but it can improve in this aspect.

I've been using it for over a year now.

The service is very stable. The only caveat is that it depends on internet connectivity. If you have a stable internet connection, you'll be able to interact with the service.

In regards to scalability, it's good because other people are hitting the service to perform their operations. The only issue would be having a stable internet connection to be able to use the tool or service to its maximum potential.

The support team is really on point. Anytime you have an issue, you reach out to them, and they are willing to understand the issue you're facing. They'll get back to you on time.

Positive

It's very easy. AWS comes with the documentation. You just go to the website, follow the documentation, and you are able to install depending on your base environment, whether you're using Linux, Windows, or macOS, depending on the operating system.

I will recommend this solution. With the pricing, it's acceptable based on what you want to achieve or your priorities at a particular time. They have options for businesses. Depending on your workload or what you intend to achieve, you can talk to the customer service team of AWS and they'll help you out. On a scale of 1-10, I rate Amazon Q a 9.

I have been using Amazon Q with Bedrock. Force Group engineering, the last company I was at, was trialing it, but it turned out to be too expensive in the end. They were going to use it with their Connect call center, but it was too expensive for what it did. This was because they needed to have the developer version, which was the most expensive option. I cannot remember the actual cost, but it was quite a lot of money when added up per user.

I do migrations and architecting and engineering. I design the migration and then implement it myself. I migrate all the client services from their in-house data center onto the AWS cloud, stage by stage.

The best feature of Amazon Q is the voice chat, where it talks back to you in normal language and you can query it. You can ask it a question and it will give you a normal answer.

Amazon Q is pretty stable since it is in general availability now. I used part of it when it was in preview, and it was somewhat unstable then. You can use it with Quicksight, which is quite a good combination. You can add Lambda functions that talk to Bedrock and Amazon Q and ask Amazon Q to do a task. It can summarize meeting minutes and create executive summaries.

Sometimes Amazon Q takes a while to get the data from the silo, from S3 or wherever it is stored, or from DynamoDB database. That could be improved by making it faster. This is one area that lets it down a little bit, as it takes a while to get the answer sometimes to the client's questions.

I have been using Amazon Q for about six months.

The initial setup and deployment of Amazon Q is not complex. I learned it and taught myself.

My impressions of the stability of Amazon Q are positive as it is quite stable now that it is in general availability. I used part of it when it was in preview, and it was somewhat unstable then.

Amazon's support team is impressive because they have 70% of the market. Microsoft Azure has about 21% and Google has about 11%, which speaks for itself. It is also the most secure network with approximately 70 security features, and there are additional features available for purchase from the AWS marketplace.

Positive

The initial setup and deployment of Amazon Q is not complex. I learned it and taught myself.

Amazon Q is good to have experience with, and I could teach it to others. I have been teaching AWS for about a year and a half through the AWS Restart course, which is a 12-week program. I am an accredited instructor for this course, and teaching someone Amazon Q and Bedrock would not be difficult.

My advice for others regarding Amazon Q would be to explore all the features, including voice and chat capabilities, executive summaries, meeting minutes, creating bullet points from meetings, and voice and chat activations.

I would definitely recommend this product to other people. On a scale of one to ten, I would give Amazon Q a rating of nine.

I used Amazon Q in my hackathon, and after that, I have not used it. For automating coding tasks and implementing AWS services in my project, I used Amazon Q Developer. I did not use Amazon Q Developer for my organization but rather for one of my hackathon projects.

Amazon Q saved my time more than other products, such as GitHub Copilot, because it is conscious about particular AWS services. If I encounter any error, it provides a perfect solution that I can follow to resolve the issue.

The best feature of Amazon Q is that it has the data of all AWS services which it processes using RAG. By performing RAG on the particular data, it is specialized for AWS services. If you want to integrate AWS services in your project, then Amazon Q Developer is the best product available.

One of the best features of Amazon Q is the inline coding, which I appreciate.

Amazon Q saved a considerable amount of time.

Amazon Q Developer is only personalized for AWS, but I hope it can be personalized for other areas, such as Google Cloud service or Azure Cloud service. Amazon Q Developer provides only one LLM model, which is Amazon's LLM. However, GitHub Copilot provides a list of LLMs, allowing users to choose their preferred LLM, which is not possible in Amazon Q Developer.

In coding terms, sometimes I do not trust Amazon Q Developer's coding suggestions.

I used Amazon Q in my hackathon, and after that, I have not used it.

We completed the project within one month. If we had not used Amazon Q Developer, it would have taken three or four months. On a scale of 1-10, I rate Amazon Q an 8.