OCI Language is a cloud-based AI service for performing sophisticated text analysis at scale. Use this service to build intelligent applications by leveraging REST APIs and SDKs to process unstructured text for sentiment analysis, entity recognition, translation, and more.
OCI Language identifies the language of your text from more than 75 languages. It also automatically recognizes at least 18 entity types including the names of people, locations, products, and organizations.
Analyze the mood or tone of the text with APIs that help extract the sentiment of individual aspects in the text across languages. OCI Language classifies results as positive, negative, and neutral sentiments with a confidence score.
Identify and classify textual content from multiple languages into more than 600 categories. Use state-of-the-art natural language processing to identify the most salient key phrases in your documents.
Easily train custom classification models to group text records into specific categories. These models are trained on your own data to meet your unique business needs.
You can train prebuilt entity models and custom models to identify terms unique to your domain, such as product part codes, manufacturing terms, and specific financial entities.
Use state-of-the-art neural machine translation to translate text between more than 20 languages.
Automatically translate conversations, applications, websites, support tickets, or any text that requires a different language.
OCI Language upholds customer privacy with language models that don’t store data for training, debugging, or other purposes. In addition, you can use OCI Language to identify any potential personally identifiable information to protect your own customers’ privacy.
OCI Language is a versatile service that can be called via REST APIs, seven different SDKs (including Python, C#, and Java), or the OCI command line. Developers can easily deploy a scalable language service without having data science or machine learning expertise.
Assess the sensitivity of documents and detect the presence of personally identifiable information (PII) to anonymize private information through masking, removal, or replacement before storing the data or circulating it to a wider audience.
Explore how customers perceive your brand, extract sentiments about specific areas of interests, and identify your customers’ top frustrations to address them early on.
Track the topics most discussed in social media or in your support knowledge base and prioritize responses based on critical areas of interest.
Extract named entities from your customer feedback to identify people, products, and organizations mentioned.
Identify frustrated customers in real time and let your most experienced agents help them.
Automatically extract key phrases from support tickets in order to find tickets that deal with similar issues or topics.
Automatically detect the language and route your support tickets to the agent that speaks it.
Comply with regulations such as GDPR by identifying PII from your data so that you can redact it before publishing.
Akshai Parthasarathy, Product Marketing Director
Sunjay Chopra, Product Marketing Manager
Learn how Now Optics was able to improve their customer engagement and experience by using state-of-the-art pretrained models in OCI Language to extract aspects and sentiments for customer reviews, as well as automatically extract entities, such as names of people, facilities, and products, from each of the records.