Glean is an AI-powered workplace search tool that supports search across all of a company's apps, centralizing company knowledge and helping employees to more quickly find what they need, with 100+ connectors.
$12
per month
IBM Watson Explorer
Score8.4 out of 10
N/A
IBM Watson Explorer supports enterprise search with unstructured data analysis, machine learning, and content analysis to improve decision-making, support customer service or serve other business needs.
Based on my experience, Glean is well suited for scenarios where you need to search through large amounts of information in a structured format, such as Confluence pages, knowledge bases, or other similar repositories. Glean's search algorithms make it easy to find the exact information you need, even if it's buried deep in a document or spread across multiple pages. On the other hand, Glean may be less appropriate for scenarios where you need to search through unstructured data, such as messages. While Glean can still be useful in these cases, its effectiveness may be limited.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
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.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
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.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
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.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
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.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
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.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
