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Oracle Cloud Infrastructure (OCI) Data Labeling is a service for building labeled datasets to more accurately train AI and machine learning models. With OCI Data Labeling, developers and data scientists assemble data, create and browse datasets, and apply labels to data records through user interfaces and public APIs. The labeled datasets can be exported for model development across Oracle’s AI and data science services for a seamless model-building experience.
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Oracle Cloud Infrastructure (OCI) Generative AI Agents is a fully managed service that integrates large language models (LLMs) with retrieval-augmented generation (RAG) capabilities, enabling users to interact with enterprise data through natural language queries. This service allows organizations to build, deploy, and manage AI agents at scale, facilitating dynamic, multi-turn dialogues and providing context-aware, accurate responses. OCI Generative AI Agents addresses the challenge of efficiently accessing and utilizing vast amounts of enterprise data. By enabling natural language interactions with data stores, it democratizes data access, reduces the need for specialized technical skills, and accelerates decision-making processes. This service is particularly beneficial for optimizing customer support, expediting legal research, enhancing revenue intelligence, and streamlining recruitment processes, thereby improving operational efficiency and customer satisfaction.
Oracle Cloud Infrastructure (OCI) Generative AI Agents is a fully managed service that integrates large language models (LLMs) with retrieval-augmented generation (RAG) to enable users to interact with enterprise data through natural language queries. This service allows organizations to build, deploy, and manage AI agents at scale, facilitating real-time, context-aware responses and actions based on up-to-date information. OCI Generative AI Agents democratize access to enterprise data by allowing users to interact with complex datasets through natural language, eliminating the need for specialized technical skills. This capability enhances productivity across various departments by enabling faster decision-making and more efficient workflows. For instance, in customer support, the service can optimize call center operations by providing accurate and timely responses, thereby increasing customer satisfaction. In legal research, it expedites the retrieval of relevant case law, reducing the time spent on manual searches. Overall, OCI Generative AI Agents empower organizations to leverage their data assets more effectively, driving innovation and competitive advantage.
Oracle Communications Billing and Revenue Management (BRM) provides a fully convergent charging and billing system to manage the entire revenue management lifecycle. From a single modular platform BRM supports charging and rating for any service, any network, any payment method, any geography and supports all customer and partner type. The solution is built with adherence to industry standards to enable application extensions for specific communications capabilities, and with pre-built integrations, through Oracle Application Integration Architecture (AIA), to key Oracle business applications such as Oracle's Siebel CRM and Oracle E-Business Suite.
Oracle Cloud Infrastructure (OCI) Generative AI is a fully managed service that provides state-of-the-art, customizable large language models (LLMs) designed to address a wide range of enterprise use cases, including text generation, summarization, and embedding creation. This service enables organizations to seamlessly integrate advanced language comprehension capabilities into their applications, enhancing productivity and decision-making processes.
Oracle Intelligent Data Lake is an integral component of the Oracle Data Intelligence Platform, designed to unify and streamline data management by integrating diverse data sources into a cohesive environment. Leveraging open-source standards such as Apache Spark and Apache Flink, it facilitates advanced data processing and real-time analytics. The platform offers a unified developer experience, incorporating a comprehensive data catalog and Jupyter Notebook for in-depth data analysis and visualization. With robust security measures, including fine-grained, role-based access controls, Oracle Intelligent Data Lake ensures secure data storage and sharing, effectively eliminating data silos and enhancing decision-making processes.
Oracle AI Vector Search, introduced in Oracle Database 23ai, empowers organizations to perform AI-driven similarity searches directly within their existing database infrastructure. By integrating vector search capabilities natively, it eliminates the need for separate vector databases, thereby reducing complexity and enhancing security. This functionality enables semantic searches across both structured and unstructured data, facilitating more sophisticated AI applications. Additionally, it supports retrieval-augmented generation (RAG), allowing large language models (LLMs) to deliver more accurate and contextually relevant results by leveraging enterprise data. Key Features and Functionality: - Native VECTOR Data Type: Store vector embeddings directly within tables, supporting various dimension counts and formats to accommodate different embedding models. - Flexible Vector Generation: Import embedding models using the ONNX framework or utilize database APIs to generate vectors from preferred embedding services. - Vector Indexes: Accelerate similarity searches with specialized indexes, such as in-memory neighbor graph indexes for high performance and neighbor partition indexes for large datasets. - Intuitive SQL Querying: Perform similarity searches using simple SQL queries, seamlessly combining vector data with relational, text, JSON, and other data types. - Retrieval-Augmented Generation (RAG): Enhance LLM interactions by providing context-specific private data, improving the accuracy of responses through combined similarity and business data searches. - Industry-Leading Security: Leverage Oracle's robust security features, including encryption, data masking, and access controls, to protect data while utilizing advanced AI search capabilities. Primary Value and User Benefits: Oracle AI Vector Search addresses the challenge of integrating AI-powered similarity search into existing business data systems without the overhead of managing multiple databases. By embedding vector search capabilities directly into Oracle Database, it simplifies application development, enhances data security, and ensures consistency. Users can perform semantic searches across diverse data types, leading to more relevant and accurate insights. Furthermore, the support for RAG enables organizations to improve the performance of LLMs by grounding them with enterprise-specific data, reducing inaccuracies and enhancing decision-making processes.
Bliva offers software services based Oracle Technology and AWS.
Oracle Reviews
Verified User in Individual & Family Services
Intuitive & Easy
Verified User in Retail
Huge Automation Potential with Phenomenal Flexibility
Leo L.
Cloud Computing, Data Analytics, AI, Machine Learning, over 25 years global e-commerce & Omni-channel experiencePowerful Reporting and Audit Controls, but a Steep Learning Curve and High TCO
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What is Oracle?
Oracle Corporation develops, manufactures, markets, hosts, and supports database and middleware software, applications software, and hardware systems.