Google Gemini (formerly Bard) is an AI assistant, presented as a creative and helpful collaborator. Gemini for Workspace is available via two plans: a Gemini Enterprise add-on, and a Gemini Business add-on.
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IBM watsonx Code Assistant Portfolio
Score 8.9 out of 10
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IBM watsonx™ Code Assistant for Red Hat® Ansible® Lightspeed demystifies the process of Ansible Playbook creation through generative AI-powered content recommendations. Purpose-built to accelerate IT Automation, the product is designed to deliver automation content recommendations for an enhanced Ansible experience.
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Pricing
Google Gemini
IBM watsonx Code Assistant Portfolio
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Google Gemini
IBM watsonx Code Assistant Portfolio
Free Trial
No
Yes
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
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Community Pulse
Google Gemini
IBM watsonx Code Assistant Portfolio
Considered Both Products
Google Gemini
Verified User
Anonymous
Chose Google Gemini
I like the fact that Gemini gives you 3 options of possible answers, and if they don't fit your needs, you are able to have other 3, until you get the best result. I have seen that the results that Gemini provides are more accurate than others. It also evolving frequently and …
Gemini seems very simple to use, veyr similar to ChatGPT, I wish they did have a capability such as ChatGPT projects one, so one can separate topics easily, it's very customizable, where I believe it defeats the others is that, is already very simple to use all of Google …
Google Gemini, when compared to other AI Tools, can be rated as follows. - Creativity: Best - Product Research: Best - User Interface: Best - Features: Very Good - Code Generation: Very Good - Documentation: Very Good - Accuracy: Good - Speed: Good Considering the above …
Google is free and included in my workspace subscription. Claude has no image generation. Google Gemini is also a Google product, so I assume it will be able to have a better understanding of the areas on Google I am trying to market. Overall, I think it's better than Claude, …
Hootsuite's OwlyGPT is great for social listening data, but Gemini is far ahead in terms of caption writing and other writing needs. Even for content creation ideas, I'd rather take the social listening insights then feed that to Gemini.
Gemini can fix its hallucination and generic output problem to get at part with Perplexity. Additionally, to beat in web search, it can produce citation after every information given. By this it can gain users trust. Sometimes, it doesn't give output only. such instances can be …
Google Gemini has the best context window in the market, the parameters are incredible and the speed is fantastic. It will lose for ChatGPT by seniority. It has the same tools now and the integration with the Google environment makes adding AI to any project, seamless. It is …
I like the UI of Google Gemini way more, and I also love the inbuilt integrations it has with open google docs and sheets. ChatGPT does not have (AFAIK) a Deep research section. Google Gemini Gems is also an awesome addition which helps to automate mundane/repetitive tasks. I …
Best at productivity based tasks that I encounter in the workplace. I spend about 20% of my time developing, and a majority of it doing overhead or operational tasks. Google Gemini is the best for analyzing spreadsheets, performing forecasting tasks, etc. If I was more …
Google Gemini stands tall in this league of AI chat tools. It has a good clean interface and good ability to answer questions quickly on questions related to research and development. However, It lacks integration with IDE tools such as Chat GPT's integration with Microsoft …
Google Gemini does pretty well against ChatGPT in regards to the information sourced and accuracy. Gemini's user interface is about the same, however I find it a bit cleaner, especially the way information is outputted. We use a lot of the Google Suite products, so access to …
Google Gemini has the advantage of being integrated with the Google family of products, very well know and used world abroad. Like, using workspace, Gemini can read my email and make a daily summary, search for urgent and important stuff, etc. Also, Gemini allows me to do …
Security is very important in the mainframe world. At Watsonx, we work in the trusted Z environment, which has strong security rules, stricter than those of other cloud-based solutions. My domain is primarily mainframe modernization and Watsonx Code Assistant for Z is …
The code generation feature in Claude works very well, but is much more bare bone than watsonx Code Assistant Portfolio. IBM watsonx Code Assistant Portfolio tries to be user friendly by providing chat-based interaction with your code and other nice UI functionalities.
Google Gemini AI features a Deep Research feature that helped us conduct thorough product research. We wanted to minimize the costs incurred by using SSL certificates in our organization, but we lacked knowledge on the subject. Google Gemini Deep Research did a thorough analysis and suggested ways to cut costs by switching vendors and using DV-type and/or wildcard SSL certificates. We also use Google Gemini for assistance during software development. However, Google Gemini seems to have limitations when suggesting code snippets for the Microsoft ecosystem.
I would recommend for understanding your Mainframe components not for the GenAI piece involved from just my experience. The explanations were not up to the quality we wanted but its deterministic side provided a lot of value for different members of my team. The visuals would be great. I am not sure where it currently stands
Deep research for getting first business research draft from Gemini, post which i use series of prompts to improve it and use my understanding to refine it further
Canvas to produce structured business topic research and newsletter. Direct edits to the sections and making client ready reports
Learning mode to get help on step by step automation of AI workflows
It can automatically revamp specific parts of the COBOL code and very useful when we want to maintain the existing codebase but improve its structure. I can highlight a block of COBOL code and use Watsonx Assistant to suggest ways to simplify and optimize it.
Legacy codes, mostly written in COBOL, are cryptic and difficult to understand. Watsonx Assistant analyzes the code and provides insights into its functionalities and dependencies. A great help when working on older applications where understanding the codebase is crucial.
A step-by-step approach to modernize our applications slowly and steadily, so that we can control the process better. I don't have to change everything at once. Instead, I can focus on specific COBOL modules and automatically convert them to Java.
Currently the document database caps out at 10, requiring us to condense some of our policies
It's large context window is a blessing and a curse. Sometimes it stops generating half way through a very ambitious request as it delivers page after page of content
There is no way to share Gems currently, so we have to publish guides to our employees on how to best configure them
It is simple, has the same standard industry format, all the tools are accessible and recognizable. Whenever we are in the browser we can switch from one request to another while the first is still running. Little hallucination and the context window has no competitor on the market right now. The pricing is also the biggest advantage.
Gemini seems very simple to use, veyr similar to ChatGPT, I wish they did have a capability such as ChatGPT projects one, so one can separate topics easily, it's very customizable, where I believe it defeats the others is that, is already very simple to use all of Google ecosystem, such as Drive, docs, sheets and else
Security is very important in the mainframe world. At Watsonx, we work in the trusted Z environment, which has strong security rules, stricter than those of other cloud-based solutions. My domain is primarily mainframe modernization and Watsonx Code Assistant for Z is specifically used to understand and work with COBOL, the language used majorly in mainframe environments, not any general-purpose language that used in various platforms. It understands the nuances of COBOL and Assembler specific to the Z environment, something crucial for my work.
While manual review and adjustments are still needed, it's a 50-70% reduction in manual coding. Think about it - a project estimated to take a year is done in 4-6 months.
We've been able to introduce new features and improvements more quickly by updating our technology faster. One relevant example is we recently released an important update to our main product 45 days earlier than planned.
It has been a smart move and it's really paid off for our company. We've cut down a lot of time we used to spend doing things manually. We now spend our resources more wisely, work faster and finish projects sooner and as a result, we've reduced our development costs by 25%.
