#1 most frequent
United States of America
73.3%44 installations of 60
What is IBM watsonx.ai?
Watsonx.ai is part of the IBM watsonx platform that brings together new generative AI capabilities, powered by foundation models, and traditional machine learning into a studio spanning the AI lifecycle. Watsonx.ai can be used to train, validate, tune, and deploy generative AI, foundation models, and machine learning capabilities, and build AI applications with less time and data.
Categories & Use Cases
Media
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Screenshot of the foundation models available in watsonx.ai. Clients have access to IBM selected open source models from Hugging Face, as well as other third-party models, and a family of IBM-developed foundation models of different sizes and architectures.
Who Buys & Uses IBM watsonx.ai
#2 most frequent
Canada
5.0%3 installations of 60
#3 most frequent
Brazil
3.3%2 installations of 60
Pros
- Strong AI model capabilities including training, adaptation, and deployment
- Valuable prompt engineering features such as prompt tuning and prompt hub
- Time and cost savings through automation and streamlined infrastructure
Cons
- Accessibility and ease of use can be challenging
- Integration with existing infrastructure can be difficult
Your NextGen AI ecosystem
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.
Pros
- Integration with other systems
- Deployment option within same exosyatem is great and can easily deploy any model .
- Security layer for governing and hace insights to see the predictions and ai studio is also good
Cons
- IBM watsonx.ai is expensive than other platforms.
- Limited integraions though it has many but still some tools integrations not there for medical usecase
- Its little difficult to learn as right now not many open reseouces
- Community is not that strong to get any answer
Return on Investment
- For one of the usecase we were able to save 1.3 million dollar by creating the COB project in 2 months by leveraging the whole ecosystem and savibg of approximately 2800 hrs per annum
- For the icd usecase wherre we have used the graph memgraph using docker to deploy it and created graphs and then created inference pipeline saved 20 minutes per medical coder and approximately of 3.5 million dollar savings as claims submission verifying on the payer side is a lengthy process
Other Software Used
IBM Watson Natural Language Understanding, IBM Watson Speech to Text, IBM Watson Visual Recognition (discontinued)
How IBM watsonx.ai changed our predictive gain
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.
Pros
- Autoprompt and tuning studio
- A built in governance checking system
- Its efficiency at training custom models
Cons
- It's currently so hard to visualize trends beyond basic plots
- Integration with non-IBM ML frameworks is quite patchy
Return on Investment
- Model retraining times have gone down, we can now refresh models twice as often as we used to
- The model generated alerts reduce last minute reassignments
Other Software Used
IBM watsonx.data
Ai Powered security analytics that strenghten detection accuracy
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
Pros
- AI driven LOG ANALYST and Investigation processing large volume of alerts and security events for incident categorisation and its identification that helps to detect attac at earlier stages of security incidents
Cons
- while AI driven insights are accurate the reasoning behind alert prioritization or anomalu scoring is somtimes opaque analyst often need more transperancy into why specific event was flagged or how a confidance score was derived
Return on Investment
- Significant time saving in alert triage and investigation
- Improved accuracy and reduced false detections
IBM watsonx.ai in Action
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.
Pros
- It understands natural language questions, so I can ask things in plain English and still get answers.
- Quickly scans through huge amounts of data
- Integration is pretty well
Cons
- Training it on our internal unique data took longer than expected
- Could have a better intuitive interface
- Customising responses for different departments can be tricky and sometimes require technical help
Return on Investment
- Reduced workload on support team, was able to automate.
- Faster response time
- Integration is great
Other Software Used
IBM Planning Analytics, IBM watsonx.data
IBM watsonx.ai Data review
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
DEsde El area de Data Science usamos IBM watsonx.ai para PoCs con el negocio
Pros
- Recognizes invoices
- Easy to prompt
- Does not hallucinate
- REconoce facturas
- Facil de promptear
- No alucina
Cons
- It's a little high the price
- Es UN Poco elevado El precio
Return on Investment
- We managed to match the competition with a new functionality
- Logramos equiparar a la competwncia con una funcionalidad nueva
