IBM Watson Discovery vs. Inbenta Enterprise Search

Overall, IBM Watson Discovery is an amazing technology that we use with our clients to address various business problems, but the biggest challenge has always been about ingesting, analyzing, enriching, and searching huge collections of documents and allowing our end users and SMEs to be able to search for what they need to reduce the time and efforts spent daily on a manual search through various collections of documents. We have successfully managed to reduce manual work by over 80%, and now our SMEs are being used for the skills they have to gather insights rather than do manual work.

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If you are looking for an enterprise search platform that offers an easy to use interface and if high performance is not really your priority, then I believe Inbenta Enterprise Search would fit your use case. For most other situations, I would recommend using a tried and tested search platform like Apache Solr.

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• It is an excellently fast platform with documents and the answers to queries.
• With automation learning beneficial as it saves time.
• When searching for a document, everything stays located and easy to find.
• Acceptance of various documents.
• It has a quite comfortable Technical support, always available when required.

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• Fairly easy to use interface.
• Quick to onboard new users, both in terms of access as well as training.
• The NLP-based semantic search feature is quite impressive.

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• I believe AI should be more flexible about providing data. However, it's understandable that you need to provide the details you need in a more specific and detailed way.
• The interface could use more tweaking. Being new to the program, it was kind of hard to navigate.
• Luckily, there was a customized feature of the dashboard that I could set up, and having something that you know where you are placed always feels familiar and comfortable.

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• It is a fairly new tool in the market, so not much market feedback exists for this. This made us apprehensive in using it.
• The documentation and online forums are bare minimum.
• Quite buggy when working with multiple sources.

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IBM Watson Discovery has the best user capabilities and easily transform business decision-making portfolio. The automation system saves time used in data analysis as opposed to manual research that consumes a lot of time. The visualization across the dashboard enables my team to interpret complex data and use it to make reliable marketing decisions.

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Similar to all IBM Watson and Salesforce product solutions, the overall support would be a 10/10. Their provided FAQ's help with frequently experienced issues and if still unable to figure something out, their customer service representatives are always super responsive. With instant chat functions available, it is easy to ask a quick question rather than sitting on hold.

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Discovery differs from its competitors due to the better ease of implementation and the high level of natural language recognition, it is equal in integration resources such as API and workflow or process pipeline, but it loses in the price for a high volume of documents and/or research. If you own or plan to use other services from the IBM Watson family, there is no doubt that Watson discovery is your best option. Another important point is if you plan to use a cloud or on-premise service (local server or private cloud).

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Apache Solr to Inbenta is like Java to Python. Apache Solr is powerful and handles complex search platforms well. Inbenta, on the other hand, is meant to be easy to use and does not lay too much emphasis on performance. If you are a small or medium business, Inbenta may suit your needs better. However, if you wish to manage a large and complex search platform, Solr is the way to go.

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• We find its Enterprise plan expensive for a country of LATAM. For US or Europe based businesses, looks great.
• A Big Data and massive queries based company would find the service expensive. Maybe a flat price plan would be helpful.
• Have you thought in making a cheaper plan where you take the learning from your customer's data to enrich your AI tool?

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• Enabled our developers to quickly deploy changes to the search model.
• NLP-powered semantic search feedback provides good actionable insights.

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Independently Invited by TrustRadius

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