Azure AI Document Intelligence vs. IBM Watson Discovery

Document Intelligence has been helpful tool in building run books and operation docs for various infrastructure platforms, the turnaround time in building & accuracy of these docs has been a great time saver for the team. When dealing with unstructured docs with no predictable format it will not understand the relationship to the desired doc you are trying to build.

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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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• From the Image the OCR technology use to store embedding properly
• From the images the OCR technology automatically capturing text is brilliant
• Also for creating Azure AI Document Intelligence endpoint and keys it is very easy to do

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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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• Azure AI Document Intelligence should have used to store image based embedding for multiple languages
• Images storing part is a different area in our case and only for a few images that part can be increased
• Cost is high which should be reduced so more users will come and more technology through this will come

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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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Very good product and will continue to evolve as it's gets refined.

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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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Being a large Microsoft customer ultimately the interoperability with the Microsoft ecosystem was the deciding factor to stay unified

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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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• Significant reduction in manual processing cost by 40-60%
• Improved data accuracy and reduce work
• Scalability is good without cost increase

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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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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