IBM watsonx.ai Reviews and Ratings

Use Cases and Deployment Scope

In our orgnisation IBM watsonx.ai is primarily used to enhance threat detection automate security analytics and it helps to improve accuracy of incident triage within our soc Operations as security analyst I leverage this platform to analyze large volume of log and alert data to interpret them against threats and malwares or malicious behaviour from Qradar logs

Likelihood to Recommend

IBM watsonx.ai is highly effective in environment where multiple security data sources generate large volume of the data and alert wherein tool will be helpful in corlate login anomalies and lateral movement detection and data access patterns to identify early signs of incidents and its alert prioritizationd and false positive refuctions helps analyst to focus on genuine alerts

Use Cases and Deployment Scope

Well, in our business we use IBM watsonx.ai for different purposes. One of them being to help our customer support team respond to inquiries faster. It can quickly scan our knowledge base and suggest helpful resources so the manual efforts has been eliminated to a large extent. We are focused on automating support and improving accuracy.

Likelihood to Recommend

We tried making an AI assistant/ chatbot out of it, worked and integrated pretty well with our process. We also use for summarising long docs, which saves a lot of time. However, the chatbot sometimes gave very generic answers, which I found to be a drawback. Also, another issue that I encountered was if the question was very complex, it started giving vague answers.

Use Cases and Deployment Scope

We use this to tune the llm, do prompting, deploy the models and then iterate for our multiple projects in medical domain like claims system, aba, chatbots etc. We are solving medical problems like medical record summarization, chatbot for QA from medical Record , ic code lookup and claims submission forms. It gives a good ecosystem of tools for miltiple usecases and all embedded within the same environment thats a great advantage and also using langchain is also great.

Likelihood to Recommend

For genai apps its very good i can say where we don't have to worry about the whole ecosystem their whole ecosystem is flawless and very powerful analytical capabilities. It maintains the data Quality and data security. When cost is concerned and when there are large data involved. It becomes costly and tuning of model is not straightforward as there is no proper active community for which we can take help

Use Cases and Deployment Scope

We have used prompt lab, the granite models, and the slate models. Prompt lab was very easy to use, and the granite models provide many options as well provide benchmarking results which is useful in picking the right models

Likelihood to Recommend

<i>Deployment, inference models</i>

Use Cases and Deployment Scope

We use IBM watsonx.ai to build, fine tune and deploy AI models that directly impact how we plan routes and manage fleet efficiency. We replaced our previous multiple standalone scripts that didn't communicate as well with a centralized IBM watsonx.ai environment.

Likelihood to Recommend

I'd say IBM watsonx.ai is 90 percent there, but advancing pretty fast. Right now, we use it to train custom models and it's really thriving. So anything custom models related will work so well. It's still struggling with managed scaling. If you can consult with expert firms, ours is Bluebay data, you'll make some really great strides.

Use Cases and Deployment Scope

We analyze logs, detect anomalies, and proactively manage database performance.

Likelihood to Recommend

It's good to have AI for log analysis and understanding bottlenecks.

Use Cases and Deployment Scope

From the Data Science area we use IBM watsonx.ai for PoCs with the business

DEsde El area de Data Science usamos IBM watsonx.ai para PoCs con el negocio

Likelihood to Recommend

It's good for AI

Es bueno para IA

<i>This review was originally written in Spanish and has been translated into English using a third-party translation tool. While we strive for accuracy, some nuances or meanings may not be perfectly captured.</i>

Use Cases and Deployment Scope

In our organization, we use IBM watsonx.ai because we need a tool for help the all business , administration , optimization and create applications

Likelihood to Recommend

In my opinion, I would likely tell a colleague that IBM watsonx.ai is a tool to help persons but I think in a implementation in a business is very difficult, implementation for consults or tutorials in a system or erp

Use Cases and Deployment Scope

Just started a new project to implement the use of IA. So long seems to be really easy to use, hope everything keeps like this, We're looking forward to get more info and more use of cases to help my organization to get in the buzz that every body talks about,

Likelihood to Recommend

I still don't have enough experience, but i've seen a lot of demos and i've made some real world scenarios and so far so long every thing looks fine, I came from Microsoft world and it's been kind of difficult to understand all the environment software and main frame focus

Use Cases and Deployment Scope

In our organization, we address business problems For Questions related to production issues with IBM watsonx.ai.

Likelihood to Recommend

In my opinion, I would likely recommend IBM watsonx.ai to a colleague because I think it Is suitable for viewing a different scenarios and their possibles aplications