4 Integrations with OCI Data Labeling
View a list of OCI Data Labeling integrations and software that integrates with OCI Data Labeling below. Compare the best OCI Data Labeling integrations as well as features, ratings, user reviews, and pricing of software that integrates with OCI Data Labeling. Here are the current OCI Data Labeling integrations in 2026:
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JSON
JSON
JSON (JavaScript Object Notation) is a lightweight data-interchange format. It is easy for humans to read and write. It is easy for machines to parse and generate. It is based on a subset of the JavaScript Programming Language Standard ECMA-262 3rd Edition - December 1999. JSON is a text format that is completely language independent but uses conventions that are familiar to programmers of the C-family of languages, including C, C++, C#, Java, JavaScript, Perl, Python, and many others. These properties make JSON an ideal data-interchange language. JSON is built on two structures: 1. A collection of name/value pairs. In various languages, this is realized as an object, record, struct, dictionary, hash table, keyed list, or associative array. 2. An ordered list of values. In most languages, this is realized as an array, vector, list, or sequence. These are universal data structures. Virtually all modern programming languages support them in one form or another.Starting Price: Free -
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Oracle AI Agent Platform
Oracle
Oracle AI Agent Platform is a fully-managed service that enables the creation, deployment, and management of intelligent virtual agents powered by large language models and integrated AI technologies. Agents can be set up through a simple few-step process, and can orchestrate tools such as natural‐language-to‐SQL conversion, retrieval-augmented generation from enterprise knowledge bases, custom function or API calling, and even the ability to coordinate sub-agents. They support multi-turn conversational experiences with context retention across sessions, enabling agents to handle follow‐up questions and maintain personalised, consistent interactions. Built-in guardrails help enforce content moderation, prompt-injection prevention, and protection of PII (personally identifiable information), while optional human-in-the-loop workflows allow real-time supervision and escalation.Starting Price: $0.003 per 10,000 transactions -
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Oracle Cloud Infrastructure
Oracle
Oracle Cloud Infrastructure supports traditional workloads and delivers modern cloud development tools. It is architected to detect and defend against modern threats, so you can innovate more. Combine low cost with high performance to lower your TCO. Oracle Cloud is a Generation 2 enterprise cloud that delivers powerful compute and networking performance and includes a comprehensive portfolio of infrastructure and platform cloud services. Built from the ground up to meet the needs of mission-critical applications, Oracle Cloud supports all legacy workloads while delivering modern cloud development tools, enabling enterprises to bring their past forward as they build their future. Our Generation 2 Cloud is the only one built to run Oracle Autonomous Database, the industry's first and only self-driving database. Oracle Cloud offers a comprehensive cloud computing portfolio, from application development and business analytics to data management, integration, security, AI & blockchain. -
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Oracle Data Science
Oracle
A data science platform that improves productivity with unparalleled abilities. Build and evaluate higher-quality machine learning (ML) models. Increase business flexibility by putting enterprise-trusted data to work quickly and support data-driven business objectives with easier deployment of ML models. Using cloud-based platforms to discover new business insights. Building a machine learning model is an iterative process. In this ebook, we break down the process and describe how machine learning models are built. Explore notebooks and build or test machine learning algorithms. Try AutoML and see data science results. Build high-quality models faster and easier. Automated machine learning capabilities rapidly examine the data and recommend the optimal data features and best algorithms. Additionally, automated machine learning tunes the model and explains the model’s results.
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