IBM Watson Explorer vs. Lucidworks Fusion

The Watson Explorer is great because it potentially replaces a meriad of other low-level analytics products that we would need to use for data analytics and data mining. WEX isn't really suitable much beyond doing text and data analytics and performing machine learning, so if your team doesn't really have a use-case that fits all of these categories, it is worth looking at an alternative.

Incentivized

Very well suited for out of the box enterprise search applications.

• Free to try - It's possible to use most of the useful features of Watson Explore on their trial/demo accounts.
• Super well-designed data analytics tool - Most of the tools and features of the explorer are really useful, and truly help you fully understand the depth of any format of textual data.
• Extensive sources compatibility - WEX can retrieve data from a large range of sources, and the compatibility there is quite good as well.

Incentivized

• Signals feature to boost search results helps search relevancy
• Business Rules feature for tuning search results
• Query pipeline design gives great flexibility in application development

• Support is just OK, like most of the other IBM Watson products. The setup/integration is really hands-on, but it's also problematic because support later may take a considerable amount of time.
• UI could still use a little more improvement - part of the administration and sources dashboards are hard to navigate.
• The Application Builder is a great part of the product, but hard to learn/understand - this is where we needed the most support from IBM and tutorials/documentation.

Incentivized

• Documentation can be improved

It is incredibly intuitive and so easy to use that business people can now complete functions that used to be limited to software developers only.

It has continued to improve over the years.

Google Cloud offers a Natural Language product, but it is just an API. This API doesn't offer the useful visualizations of relations, analytics, and graphs that IBM Watson Explorer offers on their interface. For this reason, we chose to go with IBM WEX. For later stages of our production, we decided to use Google's NLP API because we found that it was quick to integrate into production after studying data and developing models using IBM WEX.

Incentivized

IDOL seems to be a blackbox solution. Fusion is much more flexible with more features and options for developers to choose from.

• Positive - Trial/demo period. This was really useful for us to figure out what features of WEX we liked most and how difficult it would be to integrate WEX into our workflow.
• Negative - On-boarding was long and almost always requires support from IBM support, unlike most other products this advanced.
• Positive - WEX replaced a large selection of alternative products we would have to use for the same functionality, and having all of that function in one place was definitely helpful.

Incentivized

• Allowed us to move software developers from enterprise search to other customer focused applications due to built in signals processing and related popularity boosting out of the box.
• Enabled business experts to work directly with Fusion to influence search results and not be so dependent on developers.