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Rosette uses natural language processing, statistical modeling, and machine learning to analyze unstructured and semi-structured text across hundreds of language-script combinations, revealing valuable information and actionable data. Rosette provides endpoints for extracting entities and relationships, translating and comparing the similarity of names, categorizing and adding linguistic tags to text and more. Rosette Server is the on-premises installation of Rosette, with access to Rosette's functions as RESTful web service endpoints. This solves cloud security worries and allows customization (models/indexes) as needed for your business.
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Our product is a full text processing pipeline from data preparation to extracting the most relevant information and
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analysis utilizing precise, focused AI that has built-in human understanding. Text Analytics provides foundational
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linguistic analysis for identifying languages and relating words. The result is enriched and normalized text for
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high-speed search and processing without translation.
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Text Analytics extracts events and entities — people, organizations, and places — from unstructured text and adds the
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structure of associating those entities into events that deliver only the necessary information for near real-time
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decision making. Accompanying tools shorten the process of training AI models to recognize domain-specific events.
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The product delivers a multitude of ways to sharpen and expand search results. Semantic similarity expands search
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beyond keywords to words with the same meaning, even in other languages. Sentiment analysis and topic extraction help
The C# binding uses HttpClient to manage connectivity and concurrency. By default, .NET sets the default connection limit to 2, which is the same as the Rosette API default limit. For Rosette API plans that allow for higher concurrency, the internal HTTP client will adjust automatically to the higher number. If a user chooses to provide their own HTTP client, no adjustment will be made. In this case it is up to the user to set `ServicePointManager.DefaultConnectionLimit` to the Rosette API concurrency level prior to instantiating the CAPI object.
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For multithreaded operations, do not instantiate a new CAPI object for each thread. The objects will not share the connection limit and `429 too many requests` errors are likely to occur. Rather, so that the underlying HttpClient can manage the queueing of the requests across all threads, instantiate a CAPI object and pass it to each thread. If it is necessary to instantiate a CAPI object on each thread, first create an HttpClient object, either by retrieving it from an instance of CAPI via the `Client` property or by creating your own HTTP client and passing it into each thread for use by the CAPI constructor.
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The C# binding uses HttpClient to manage connectivity and concurrency. By default, .NET sets the default connection
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limit to 2, which is the same as the Analytics API default limit. For Analytics API plans that allow for higher
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concurrency, the internal HTTP client will adjust automatically to the higher number. If a user chooses to provide
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their own HTTP client, no adjustment will be made. In this case it is up to the user to set
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`ServicePointManager.DefaultConnectionLimit` to the Analytics API concurrency level prior to instantiating the CAPI object.
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For multithreaded operations, do not instantiate a new CAPI object for each thread. The objects will not share the
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connection limit and `429 too many requests` errors are likely to occur. Rather, so that the underlying HttpClient can
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manage the queueing of the requests across all threads, instantiate a CAPI object and pass it to each thread. If it is
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necessary to instantiate a CAPI object on each thread, first create an HttpClient object, either by retrieving it from
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an instance of CAPI via the `Client` property or by creating your own HTTP client and passing it into each thread for use by the CAPI constructor.
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#### Example of using a common CAPI object for each thread:
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