IBM watsonx Orchestrate vs. Splunk AI Assistant for SPL

In our case, it is well-suited for workday integration, which allows us to automate the entire workflow. However, we are still working on the O9 platform integration, which we feel is less appropriate, and integrating the workflow into the platform.

Splunk AI Assistant for SPL is well suited for people wanting to code on splunk but have limited or few knowledge on SPL requests. It can be good for people learning and training but also for business applying their own business case thanks to the AI, good for simple case scenario. However, for more complex scenario, involving for example multiple dashboard linked with workflow (get/post) and treillis, leading to other dashboard etc.. AI can be limited to the memory it can hold in.

Incentivized

• New and improved natural language processing yielding better results helps the assistants understand the intention behind the query.
• Preserves context of communication, allowing the customers to establish inquiries on the website and continue on the mobile app without having extra informational input.
• Intelligent conversations mean that complex paths that are branched based on the user's inputs allow for a much more natural flow of the conversation than fixed scripts.

Incentivized

• Create complex requests
• Optimize SPL requests
• learning and training

Incentivized

• I think that it needs to be able to integrate better with the knowledge catalogs. It currently provides a default database, which isn't quite large enough for enterprise use. We can connect that then to an external source, but it'd be nice if we could able just to instantiate one straight away.

Incentivized

• more data awareness of the issue
• explain more about best practice and performance issue in some query
• can't be used for complex panel, where it requires to check multiple panels, with multiple sources and sourcetype and complex dashboarding linked

Incentivized

Currently we are using to develop chatbots based on client provided flow what kind chatbot required for client either button or free text chatbots. we will decided accordingly flow and develop chatbot using IBM Watson. We will integrated custom components if required which is not present in library. Action flow and dialog flow we are currently in chatbot.

Incentivized

With the growing use of AI and chatbots, it's very easy to use, and the conversational language makes it easier than keyword searches in a document. The contextual language processing is impressive. It's easy to integrate into our internal portal. The use of this tool would depend on each company's security and data sensitivity.

Incentivized

Splunk AI Assistant for SPL is good tool, as I said, it is really useful for educational purpose, taking in its hands small and simple tasks (ex:small query dashboard,...), but it's not a ten because the contextual memory for complex issues/dashboarding/reports etc can be limited, and can sometime suggets none optimized query which are not always checked by teammates and can cause issue on the long term.

Incentivized

To develop chatbots based on client provided flow what kind chatbot required for client either button or free text chatbots. we will decided accordingly flow and develop chatbot using IBM Watson. We will integrated custom components if required which is not present in library. IBM Watson library anyone can easily learn and develop chatbots.

Incentivized

We've rarely had to engage support, but they've always been prompt in responding and very attentive. Support experiences have been extremely positive (but we're mostly happy that we just don't have any cause to routinely need support in the first place!).

Incentivized

Excellent course material.

Incentivized

Overall the implementation was simple.

Incentivized

Make has more community of workflows to follow that have been redeveloped and are available for download. Selecting WxO is based on our trust level with IBM and the propositions of the Granite model being less biased, more business trained, and the ecosystem allowing for expansion with Assistant and Discovery.

Incentivized

CoPilot AI and ChatGPT I think lacks context so compared to Splunk AI Assistant for SPL they almost always answer something that do not work. Gemini is better than those two but Splunk AI Assistant for SPL still have the most knowledge for SPL and suggets SPL query that always works but performance can be limited on some of these.

Incentivized

From past 3+ years I am using IBM Watson in our current project easily can implement and manage and monitor user how their using. Is there and update also just update dialog is just enough to change no need to touch any other templates. Multiple language will support, and action and dialog speak recognize chatbot we can create as per client requirement. Overall, as of now good experience with IBM Watson.

Incentivized

• By automating tasks that would otherwise require human intervention, organizations may achieve cost savings in terms of labor, especially for handling large volumes of routine inquiries.
• Virtual assistants can handle a large number of simultaneous interactions, making them scalable to accommodate growing customer bases and increasing workloads without a linear increase in staffing.

Incentivized

• Quicker training (so people are delivering way sooner) --> 2 weeks of training, now only 1 necessary
• Small and reduntant tasks done by AI, taking way much time, sometimes dividing by 2 the time
• People check less their query, which can lead to multiple rechecks and lost time

Incentivized