What is our primary use case?
I was just running a PoC with a showcase between our integration on our platform to the Watson STK essentially; using the cognitive responses that we could give it, using natural language and sentiment analysis.
Essentially, we would take natural language that was happening in our repositories and our application and then feed it to the Watson APIs, and then we would receive JSON payloads as an API response to get cognitive feedback from the repository data.
How has it helped my organization?
It's been good, it's helped further the relationship with IBM. We're also discussing feature integration points for Watson on the GitHub platform.
What is most valuable?
Ease of use is pretty good and the standardization of not actually having to have my own natural learning algorithms, just to use the Watson APIs.
What needs improvement?
More cognitive feedback would be good. The natural language analysis is great, the sentiment analyzers are great. But I would just like to see more - I don't know what those ideas are - just more innovation done with the Watson platform, that would be interesting.
For how long have I used the solution?
What do I think about the stability of the solution?
What do I think about the scalability of the solution?
As far as I know it seems scalable.
How is customer service and technical support?
I have not had to use tech support.
How was the initial setup?
What other advice do I have?
The most important criteria when selecting a vendor are their
I would rate it a seven. It's easy to use but I'm still in PoC stages.
Be sure you have an understanding or concept in terms of the goal that you want. Because if you don't have a goal in mind when using those APIs, then the data that comes back is just noise at that point.
Disclosure: I am a real user, and this review is based on my own experience and opinions.
Mar 27 2018