AI Language
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 features
Detect languages, names, places, quantities, 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 sentiment from subjective information
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.
Categorize documents and identify key phrases
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.
Custom classification
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.
Custom entity extraction
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.
Neural machine translation
Use state-of-the-art neural machine translation to translate text in more than 30 languages. Automatically translate emails, conversations, guided journeys, UI labels into 30 languages.
Purpose-built for security and privacy
OCI Language is HIPAA and FedRAMP compliant service and customer has the full control of their data.
Easy to deploy
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.
OCI Language use cases
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Customer feedback analytics
- Understand sentiment, improve experience
Explore how customers perceive your brand, extract sentiments about specific areas of interests, and identify your customers’ top frustrations to address them early on.
- Learn what your customers are saying
Track the topics most discussed in social media or in your support knowledge base and prioritize responses based on critical areas of interest.
- Identify key players from customer feedback
Extract named entities from your customer feedback to identify people, products, and organizations mentioned.
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Enhance customer support
- Identify cases that need escalation
Identify frustrated customers in real time and let your most experienced agents help them.
- Rapidly find similar support tickets
Automatically extract key phrases from support tickets in order to find tickets that deal with similar issues or topics.
- Find the right support agent language
Automatically detect the language and route your support tickets to the agent that speaks it.
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Customer privacy enforcement
- Comply with data regulations
Comply with regulations such as GDPR by identifying PII from your data so that you can redact it before publishing.
Now Optics taps Oracle’s Artificial Intelligence for insights that improve customer experience
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.
Featured blogs
- November 19, 2021 Extracting insights from unstructured data using AI services
- May 6, 2021 Announcing Oracle Cloud Infrastructure Language for AI-powered text analysis
- March 11, 2021 6 tips for easier AI adoption
Resources
Hands-on-lab
Perform NLP tasks like detecting languages, extracting key elements, classifying intent, detecting the sentiment, etc., with a few simple steps.
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