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Introduced in 2019, the Oracle Cloud AI Platform provides a comprehensive suite of tools for building, deploying, and managing Artificial Intelligence (AI) applications. It supports Machine Learning (ML), Deep Learning (DL), and Natural Language Processing (NLP) workflows. The platform integrates with Oracle Cloud Infrastructure (OCI), allowing enterprises to leverage high-performance computing resources for their AI projects.
Released in 2018, Oracle Machine Learning for SQL brings Machine Learning (ML) capabilities directly to the database. It enables developers to build and execute ML models using SQL Queries without data movement, ensuring efficiency and security. This integration supports Data Science workflows within Oracle Database environments.
Launched in 2021, Oracle AI Vision offers advanced Computer Vision capabilities, including Image Recognition, Object Detection, and Video Analytics. It is designed to process unstructured visual data and provide actionable insights across industries such as manufacturing and retail.
Oracle Digital Assistant, introduced in 2019, is a conversational AI platform for building intelligent chatbots and voice interfaces. It leverages Natural Language Understanding (NLU) and Dialog Management to provide personalized user experiences. It integrates seamlessly with Oracle's enterprise applications and external APIs.
Released in 2020, Oracle Data Science Service is a collaborative environment for Data Scientists to build, train, and deploy Machine Learning (ML) models. It supports popular frameworks like TensorFlow Framework, PyTorch Library, and Scikit-Learn Library, allowing users to bring their tools to Oracle Cloud Infrastructure (OCI).
Launched in 2018, Oracle Autonomous Database integrates Machine Learning (ML) capabilities to automate routine tasks like indexing, patching, and performance tuning. It includes in-database ML algorithms, enabling Predictive Analytics and anomaly detection directly within the database environment.
Introduced in 2021, Oracle AI Language provides Natural Language Processing (NLP) capabilities for text analysis, including Sentiment Analysis, Entity Recognition, and text summarization. It supports multiple languages and integrates with other Oracle services for comprehensive text-based analytics.
Oracle AI Speech, released in 2021, offers advanced Speech Recognition and Text-to-Speech (TTS) capabilities. It supports transcription, voice command applications, and multilingual voice generation, making it suitable for customer service and accessibility solutions.
Launched in 2020, Oracle AI Forecasting provides AI-driven tools for demand forecasting and resource planning. It employs Time Series Analysis and Predictive Analytics to help businesses optimize inventory, pricing, and supply chain operations.
Introduced in 2020, Oracle Cloud Infrastructure Data Labeling is a tool for creating labeled datasets to train Machine Learning (ML) models. It supports annotation for text, images, and videos, integrating with Oracle’s AI services for seamless ML pipeline development.
https://www.oracle.com/data-labeling
Introduced in 2021, Oracle Cloud Infrastructure AI Services provides pre-trained AI models and tools for building and deploying Machine Learning (ML) solutions. It includes services for Natural Language Processing (NLP), Computer Vision, and Speech Recognition, allowing developers to integrate AI capabilities into applications with minimal effort.
Released in 2019, Oracle Machine Learning Notebooks is an interactive environment for Data Scientists and developers to build, evaluate, and deploy Machine Learning (ML) models. It supports scripting in Python Programming Language and SQL Queries, providing flexibility in Data Science workflows.
Launched in 2021, Oracle Cloud Infrastructure Anomaly Detection uses AI to identify unusual patterns in data. It supports applications in fraud detection, predictive maintenance, and cybersecurity, providing pre-built models for rapid deployment.
Oracle AI Demand Forecasting, introduced in 2020, helps organizations predict future demand using Predictive Analytics and Time Series Analysis. It integrates with Oracle’s supply chain management tools to improve planning and resource allocation.
Released in 2021, Oracle AI Document Understanding provides Natural Language Processing (NLP) capabilities for extracting structured data from unstructured documents. It supports applications in legal, financial, and operational data management.
Launched in 2018, Oracle Autonomous Data Warehouse includes built-in Machine Learning (ML) features to support Data Analytics and modeling. It automates data preparation and Feature Engineering tasks, accelerating AI and ML workflows.
Introduced in 2020, Oracle AI Conversational Interfaces enable developers to create voice-activated and text-based AI assistants. It uses Natural Language Understanding (NLU) to enhance user interaction across enterprise applications and services.
Released in 2021, Oracle Cloud Infrastructure Vision AI specializes in Image Recognition and Object Detection. It supports tasks like quality control in manufacturing and visual search in e-commerce, leveraging Deep Learning (DL) models.
Launched in 2021, Oracle AI Model Management simplifies the deployment, monitoring, and governance of Machine Learning (ML) models. It supports MLOps (Machine Learning Operations) to ensure seamless lifecycle management in enterprise environments.
Introduced in 2020, Oracle Cloud Infrastructure Data Science Pipelines provides an end-to-end framework for building and deploying AI workflows. It automates ETL Processes (Extract, Transform, Load) and integrates with other Oracle AI services for streamlined operations.
https://www.oracle.com/data-science-pipelines
Introduced in 2021, Oracle Cloud Infrastructure AI Text Analysis provides Natural Language Processing (NLP) capabilities for processing and analyzing text. It supports Sentiment Analysis, Entity Recognition, and custom text classification for industries like finance, healthcare, and retail.
Released in 2020, Oracle AI-Powered Workflow Automation uses AI to streamline business processes and optimize task management. It integrates with Oracle’s suite of enterprise applications to automate repetitive tasks, improving productivity and reducing errors.
Launched in 2021, Oracle Cloud Infrastructure AI Custom Vision allows users to train and deploy Computer Vision models tailored to specific use cases. It supports Image Classification and Object Detection for applications in manufacturing, retail, and healthcare.
Oracle AI Edge Analytics, introduced in 2021, brings AI and Machine Learning (ML) capabilities to edge devices. It supports real-time data processing and analysis, enabling faster decision-making in IoT and industrial environments.
Released in 2020, Oracle AI Energy Insights applies AI and Predictive Analytics to monitor and optimize energy consumption. It is designed for industries like utilities and manufacturing to reduce costs and support sustainability initiatives.
Launched in 2021, Oracle Cloud Infrastructure Speech Translation combines Speech Recognition and Natural Language Processing (NLP) to provide real-time multilingual speech-to-text translation. It supports global business communication and accessibility solutions.
Introduced in 2020, Oracle AI Security Analytics uses AI and Anomaly Detection to monitor and secure enterprise systems. It integrates with Oracle’s cloud security tools to detect threats and automate incident responses.
Released in 2021, Oracle Cloud Infrastructure AI Data Augmentation provides tools for enriching datasets for Machine Learning (ML). It automates data labeling, synthesis, and enhancement, improving the accuracy of AI models.
Launched in 2020, Oracle Cloud Infrastructure Forecasting AI uses Time Series Analysis and Predictive Analytics to forecast trends in sales, demand, and resource allocation. It supports industries like retail, finance, and supply chain management.
Introduced in 2020, Oracle AI Financial Crime Detection uses AI to identify and mitigate financial fraud. It leverages Anomaly Detection and Pattern Recognition to monitor transactions and ensure compliance with regulatory standards.
https://www.oracle.com/ai-financial-crime-detection
Introduced in 2021, Oracle AI Image and Video Analytics provides advanced Computer Vision capabilities for analyzing visual data. It supports Object Detection, Semantic Segmentation, and video content tagging, enabling industries to automate visual workflows and derive actionable insights.
Released in 2020, Oracle AI Supply Chain Planning leverages Predictive Analytics and Machine Learning (ML) to optimize supply chain operations. It forecasts demand, reduces inventory waste, and ensures timely delivery across industries.
Launched in 2020, Oracle Cloud Infrastructure Data Preparation automates Data Cleaning, Feature Engineering, and transformation tasks for Machine Learning (ML). It integrates with Oracle’s AI and analytics tools, speeding up Data Science workflows.
Oracle AI Knowledge Management, introduced in 2021, enhances information retrieval using Natural Language Processing (NLP) and Semantic Search. It enables enterprises to organize, search, and analyze large knowledge bases effectively.
Released in 2020, Oracle Autonomous JSON Database includes AI capabilities for processing and analyzing JSON data. It supports Machine Learning (ML) model development directly within the database for modern application development.
Launched in 2019, Oracle AI for Marketing Automation uses Predictive Analytics and Customer Segmentation to optimize marketing campaigns. It personalizes messaging and boosts conversion rates through intelligent customer targeting.
Introduced in 2021, Oracle AI Conversational Models offers pre-trained Natural Language Understanding (NLU) models for building chatbots and virtual assistants. It supports integration with Oracle Digital Assistant and other conversational platforms.
Released in 2020, Oracle AI Cost Optimization Analytics uses AI to analyze operational costs and identify savings opportunities. It is designed to help businesses reduce expenses and enhance profitability.
Launched in 2019, Oracle AI Customer Behavior Insights combines Machine Learning (ML) and Big Data Analytics to understand customer behavior. It enables businesses to refine strategies based on purchasing patterns and feedback.
Introduced in 2021, Oracle AI Health Data Analytics applies AI to analyze medical data for diagnostics and treatment planning. It supports Predictive Analytics and real-time monitoring, improving outcomes in healthcare systems.
https://www.oracle.com/ai-health-data-analytics
Introduced in 2020, Oracle AI Enterprise Data Management applies AI to streamline the organization and governance of enterprise data. It supports Data Lineage, Metadata Management, and Data Quality Assurance to improve decision-making across industries.
Released in 2021, Oracle Cloud Infrastructure AI Data Security combines AI and Anomaly Detection to monitor and protect sensitive data. It helps organizations detect unauthorized access and enforce compliance with security protocols.
Launched in 2020, Oracle AI Virtual Agent Builder enables enterprises to create intelligent chatbots and virtual assistants using Natural Language Understanding (NLU). It integrates with Oracle enterprise applications for seamless customer interaction.
Oracle AI Environmental Insights, introduced in 2021, uses AI and Big Data Analytics to monitor and predict environmental changes. It supports sustainability initiatives by providing actionable insights into resource management and emissions.
Released in 2020, Oracle Cloud Infrastructure AI Recommendation Engine leverages Machine Learning (ML) to deliver personalized product and content recommendations. It is widely used in e-commerce, media, and customer engagement platforms.
Launched in 2019, Oracle AI-Powered Workforce Analytics uses Predictive Analytics to assess employee performance and retention risks. It provides actionable insights to improve hiring, training, and organizational effectiveness.
Introduced in 2021, Oracle AI-Powered Inventory Management applies AI and Time Series Analysis to optimize stock levels and minimize waste. It integrates with supply chain systems to streamline operations.
Released in 2020, Oracle Cloud Infrastructure AI Time Series Forecasting provides tools for analyzing and predicting trends in temporal data. It supports use cases in finance, retail, and energy management.
Launched in 2019, Oracle AI Risk and Compliance Monitoring uses AI to track regulatory compliance and assess risks. It supports industries such as finance and healthcare with real-time alerts and reporting tools.
Introduced in 2021, Oracle AI for Smart Cities leverages AI and IoT to optimize urban infrastructure. It supports applications in traffic management, energy consumption, and public safety, enhancing the quality of urban life.
https://www.oracle.com/ai-smart-cities
Introduced in 2020, Oracle Cloud Infrastructure AI Data Catalog enhances Data Governance with advanced AI tools for organizing, indexing, and searching enterprise data. It supports Metadata Management and Data Lineage to streamline data operations.
Released in 2019, Oracle AI Fraud Detection and Prevention leverages Anomaly Detection and Predictive Analytics to identify and mitigate fraudulent activities. It is used in financial services and e-commerce for real-time fraud monitoring.
Launched in 2021, Oracle AI Conversational Analytics uses Natural Language Processing (NLP) to analyze chatbot and voice assistant interactions. It provides insights into user behavior, improving conversational AI performance.
Oracle AI Dynamic Pricing Engine, introduced in 2020, uses Machine Learning (ML) and Big Data Analytics to optimize pricing strategies. It helps businesses adjust prices in real time based on demand, competition, and market trends.
Released in 2020, Oracle AI Cloud Monitoring integrates AI and Anomaly Detection to monitor cloud resources. It provides predictive insights into system performance, preventing downtime and optimizing resource utilization.
Launched in 2021, Oracle Cloud Infrastructure AI Personalization delivers tailored user experiences using AI and Customer Segmentation. It supports recommendations, targeted content, and adaptive interfaces in digital platforms.
Introduced in 2019, Oracle AI-Driven Customer Segmentation uses Predictive Analytics and Clustering Algorithms to categorize customers based on behavior and preferences. It supports marketing campaigns and customer retention strategies.
Released in 2020, Oracle AI Knowledge Graph Builder constructs Knowledge Graphs for linking and analyzing enterprise data. It employs Graph Neural Networks (GNNs) for advanced relationship modeling and decision-making.
Launched in 2021, Oracle AI Enterprise Search combines Semantic Search and Natural Language Understanding (NLU) to improve document retrieval. It is designed for large organizations managing extensive knowledge bases.
Introduced in 2020, Oracle AI Retail Insights applies Predictive Analytics and Time Series Analysis to optimize retail operations. It supports inventory management, demand forecasting, and personalized customer experiences.
https://www.oracle.com/ai-retail-insights