1. Oracle 台灣
  2. 雲端
  3. 人工智慧
  4. Generative AI

Generative AI Agents

Oracle Cloud Infrastructure (OCI) Generative AI Agents combines the power of large language models (LLMs) and retrieval-augmented generation (RAG) with your enterprise data, letting users query diverse enterprise knowledge bases. The service provides up-to-date information through a natural language interface and the ability to act directly on it.

Why use OCI Generative AI Agents?

  • Converse directly with your enterprise knowledge bases

    Leverage a conversational interface that lets anyone query enterprise data stores in natural language.

  • Get up-to-date results

    Receive dynamic, real-time responses, even on fast-changing enterprise data stores.

  • Embedded for actionable results

    Create and embed custom AI agents into enterprise business applications and processes.

  • Scale your search

    Get faster results through RAG with OpenSearch and AI Vector Search in Oracle Database 23ai.

How OCI Generative AI Agents works

How OCI Generative AI works technical diagram, details below

  1. Input

    The left hand side of the diagram shows an icon of a person, designating the user, underneath the text “Input”.
    1. A user’s natural language request is sent to the Generative AI agent for encoding. The agent then sends the request to the enterprise data store.

  2. Generative AI Agent

    A blue arrow then points from left to right, directing the reader to another section of the diagram. This section is titled “Generative AI Agent” and features an icon designating a cloud database, with a smaller black arrow pointing towards an icon designating Artificial Intelligence. Below these icons, the text reads “The Generative AI agent uses a large language model (LLM) to understand the query, then formulates and executes a plan to:
    1. 1. Search the knowledge base for related articles
    2. 2. Re-rank the documents for semantic relevance
    3. 3. Send the top documents and the original query to be combined into a coherent response
    4. 4. Send the response to the user

  3. Output

    A second blue arrow then points from left to right, directing the reader to the third and final section of the diagram. This section is titled “Output” and features an icon designating a chatbot typing a response. Below the icon, text reads:
    1. The user receives the formulated response and references to the documents used to create the response.

Learn about the efficiency architecture of OCI Generative AI Agents

Explore how OCI Generative AI Agents uses RAG to retrieve real-time, accurate information from your own data stores, making strategic use of data quick and easy.

OCI Generative AI Agents use cases

Call center optimization

Help increase customer satisfaction through more accurate responses and a higher volume of query resolution.

Expedite legal research

Find answers faster by conversing with AI rather than manually searching court record databases.

Revenue intelligence

Understand customer purchase history and trends by asking natural language questions instead of running reports.

Recruit qualified job candidates

Source potential new hires more easily by typing in natural language rather than constructing a database query.

What customers are saying about OCI Generative AI Agents

“The beta launch of Oracle’s Generative AI Agents RAG service is a game changer. We can’t wait to showcase this innovation to our clients across a range of industries as it is fundamental to unlocking new potential with their generative AI strategies on OCI. For example, implementing RAG is vital for enabling faster and smarter access to data and knowledge within Human Resources, Finance, and Healthcare for both structured and unstructured data sources.”

Antony Heljula
Technology Director, TPXimpact

“By accessing a wider range of information and diverse perspectives, retrieval-augmented generation (RAG) can help generate more creative and coherent outputs. This is valuable for content creation tasks like writing reports, marketing materials, and creative writing. Customer service organizations can now leverage Oracle RAG to unlock a new level of efficiency and effectiveness, enhance chatbots and virtual assistants, personalize customer interactions, and resolve inquiries with remarkable accuracy and speed.”

Imran Azhar Sheikh
Head of Artificial Intelligence, Abu Dhabi Media Network

OCI Generative AI Agents resources

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