Amazon Comprehend vs. Azure OpenAI Service

Specifically, it starts processing millions of documents in minutes by leveraging the power of machine learning without having trained models from scratch. If any of the content contains personally identifiable information not only can Amazon Comprehend locate it but it will also redact or mask it. Using NLP techniques Amazon Comprehend goes well beyond keyword search or rules-based tagging to accurately classify documents. For my task or development, I cannot find any difficulties with Amazon Comprehend.

Incentivized

The pricing doesn't seem fair to me if we compare the limitations and errors in the models. Also, they are currently working on new unified portal for all AI projects which is in beta preview. So, I guess we should wait until it matures, and fixes all the issues and should use once pricing and performance improves.

Incentivized

• Amazon Comprehend identifies the language of the text and extracts Key-phrases, places, people, brands or events.
• It can build a custom set of entities or text classification models that are tailored uniquely to the organisation's need
• Amazon Comprehend's medical can be used to identify medical conditions, medications, dosages, strength and frequencies from sources like doctor's notes, clinical trial reports and patient health records. This service is very good and with well an accuracy or confidence score.

Incentivized

• It's generative AI like ChatGPT but you get advanced models, so it's more powerful.
• You can use API to automate the process of Generative AI tasks.
• It also provides a sample script code on how we can use the API.

Incentivized

• It will be great if Amazon Comprehend provide support specifically for litigation or related text documents to extract insights from it.
• For REST API support using JAVA SDK, it will be great for developers if they provide support for testing without any credentials or account details.
• Setting up for REST API integration can be as simple as possible.

Incentivized

• The user interface is similar to the Azure, so it's bit laggy, they should improve it.
• The chat models sometimes return nothing, I guess they are still testing them.
• The models we use have quota limitation on tokens and number of requests.

Incentivized

For natural language processing tasks or techniques, there are many service providers out there in the market such as Azure Cloud Services, IBM Watson and Google Cloud Platform (GCP), but compared with them, Amazon Comprehend is the best service provider in contents of accuracy, speed of processing multilingual text, supporting SDK for most of the languages and well documented.

Incentivized

Overall, Azure OpenAI services are not worth using, but only reason I used it because I got it under Startup sponsorship from Microsoft. Pricing is very high.

Incentivized

• It supports better and accurately as compared with our existing or old implementations. So, we fulfil our needs as per clients' requirements and it will help to grow or improve client satisfaction.
• For these specific requirements, we do not require any machine learning engineers or related professionals to hire in our organisation.
• None of any negative sides can be affected our business or distract existing clients.

Incentivized

• Honestly, I just started using it a few months ago, and I haven't seen any major benefits.
• It has almost similar capabilities as free version of ChatGPT, so it's worth paying for chat models unless we need to use API.
• ROI has not been impacted at all, as I mostly use free version over this to avoid higher charges.

Incentivized