August Edition Oracle Integration Community Newsletter #233 |
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Connect HCM, CX, ERP with Oracle Integration |
| Grow the Oracle Cloud business and connect, extend & innovate Oracle SaaS solutions. |
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Dear Integration Community,
Since the launch of Oracle Integration, more than 10,000 professionals have become certified implementation experts—using that achievement to strengthen their skills, build confidence, and advance their careers. Certification is not just a badge. For me, it represents a commitment to continuous learning in a field that keeps evolving. Whether you are beginning your integration journey or expanding your expertise, the latest 2026 certification is a valuable opportunity to validate what you know and open new professional doors. Don’t miss the chance to take the next step: explore the latest 2026 Oracle Integration certification.
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Table of Content |
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Announcements
Integration section
Community information
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Build Agentic HCM Experiences on Your Existing Investments |
August 25th 2026 |
| Organizations have invested years automating HCM business processes with Oracle Integration |
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Connecting Fusion HCM with identity, recruiting, document management, IT service management, productivity, and other enterprise applications. As enterprises adopt AI agents, those investments do not need to be rebuilt.
In this session, learn how you can use your existing Oracle Integration platform, connections, integrations, mappings, and automation assets as the foundation for agentic HCM experiences built with Fusion HCM Agent Studio. We’ll show how Oracle Integration can expose existing HCM automations as governed, agent-ready business capabilities, allowing Fusion HCM agents to retrieve information, reason over business context, identify exceptions, and initiate approved actions across connected applications.
Through a worker-onboarding demonstration, you’ll see how an existing multi-application HCM process can be given an agentic experience without recreating the underlying integrations. Discover how Oracle Integration can help you evolve from traditional HCM process automation to agent-driven automation while preserving your existing investments, enterprise governance, security, observability, and connectivity.
Speakers: Madhav Poosarla and Prakash Masand
Schedule: August 25th 2026 7:30 – 8:30 PST (Los Angeles time) 16:30 - 17:30 CET (Berlin time) 20:00 - 21:00 IST (Bengaluru time)
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Take the opportunity to watch our community webcasts on-demand: |
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Oracle Integration Bootcamp Connect SaaS & Agentic AI |
free hands-on training |
| 3-day hands-on Oracle Integration Bootcamp designed for consultants, architects and developers. |
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Get started with Agentic AI and Oracle Integration |
free hands-on Oracle LiveLabs training |
| Oracle Integration 3 - Intelligent Expense Automation with Agentic AI. |
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Certifications Oracle Integration |
free certification |
| At the Oracle Learning Center partners can attend free online classes and certifications. |
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Enablement and certification are key to cloud success: |
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Resources Oracle Integration Partner Community |
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Want to attend an event, receive a newsletter, collaborate via cloud customer connect or ask your questions?
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| Links, certifications, events & training calendar. |
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Accelerating Enterprise Automation using Agentic AI in Oracle Integration by Biman Sarkar, Prakash Masand, Venkat Chowdhury
Introduction:
Enterprise automation is changing as AI becomes a core part of how systems and processes work together. Instead of depending only on fixed, rule-based workflows, organizations are using AI to make automation smarter, more flexible, and easier to scale. Oracle Integration addresses this transformation by integrating Agentic AI into its platform, embedding intelligence across design and development phases of the integration lifecycle to simplify and scale enterprise automation.
In this blog, we demonstrate how AI Agents transform a flight booking architecture by shifting it from manual or rigid, rule-based workflows to intelligent, adaptive orchestration where the business provides tools, human tasks, and a knowledge base. The AI agent then decides how to execute the task. Instead of following a predictable automation sequence, like “get flight → approval → booking” the AI agent understands user intent, evaluates travel policies, chooses the best flight options, determines whether approval is required, and adapts its next action based on outcomes such as rejection or budget constraints. By reasoning over context and invoking integrations such as flight search, approval workflows, and booking systems as tools, the AI agent enables faster bookings, consistent policy compliance, involve human approval and delivers a more personalized, conversational travel experience while keeping the underlying systems modular and reusable.
Components:
Oracle Integration offers a wide range of automation capabilities to translate agent intent into actionable outcomes. The LLM provides reasoning to the agent, while Oracle Integration provides execution.
AI Agents: Oracle has recently added a comprehensive suite of agentic AI functionalities to expose enterprise actions and data as tools, enabling AI Agents to invoke these tools within any MCP-compliant ecosystem. For example, AI agents determine which integrations to use and in which order to achieve an end-to-end flight booking process without relying on a fixed workflow. You may refer to the Oracle Blog here for more details about the AI Agent.
Connecting Oracle AI Data Platform Agent Flows to OIC MCP Tools for Enterprise Automation by Sandhya Lakshmi Gopalan
Oracle AIDP enables agent flows that reason over governed enterprise data. Oracle Integration Cloud extends those flows by exposing integrations as governed, callable MCP tools, allowing agents to take controlled, policy-aware, and auditable actions across Oracle and non-Oracle enterprise applications and systems.
What Is Oracle AIDP?
Oracle AIDP provides the foundation for building enterprise agent flows that are grounded in trusted data and governed business context. Rather than treating AI agents as standalone assistants, AIDP enables them to reason over enterprise data, apply business rules, make policy-aware decisions, and invoke tools to complete business workflows.
AIDP is built around a governed data foundation. Using a medallion-style architecture, data can be organized across Bronze, Silver, and Gold layers. Bronze preserves raw, source-aligned data, Silver applies cleansing and standardization, and Gold exposes curated, business-ready data products for consumption by analytics, applications, and agent flows.
This is where Master Catalog plays an important role. Master Catalog helps agents and users discover trusted enterprise context across structured and unstructured sources without requiring unnecessary data replication. Structured data such as purchase orders, suppliers, invoices, and finance records can be cataloged alongside unstructured content such as policies, contracts, SOPs, and documents. The data can remain where it lives, while Master Catalog provides the governed discovery, metadata, lineage, and access context needed to use it responsibly.
Together, the medallion architecture and Master Catalog help AIDP give agents access to trusted data products and contextual knowledge. Instead of every agent flow building direct integrations into raw systems, agents can reason over governed, reusable enterprise context before taking action.
This makes AIDP more than an agent orchestration layer. It becomes a governed data and agent platform: one that connects trusted enterprise knowledge with policy-aware agent flows and controlled tool execution.
From Headset to ATP: How OIC Turns Support Calls into Searchable Knowledge by Biman Sarkar and Madhav Poosarla
Introduction
Every support call your team handles is a small goldmine. A customer describes a real-world problem in plain language, an agent troubleshoots it live, and a resolution emerges. Then the call ends, and most of that knowledge evaporates. At best it survives as a few terse lines in a ticket; at worst, it is gone the moment the headset comes off. What if every call automatically became a clean, timestamped, speaker-separated transcript, written straight into Oracle Autonomous Database (ATP), ready to power semantic search or ground an OCI Generative AI Agent for Retrieval-Augmented Generation (RAG)?.
This is where Oracle Integration (OIC) earns its keep. OIC is the engine that makes the whole thing effortless: it takes a recording sitting in object storage, hands it to OCI AI Speech to convert speech into text, waits for the transcription to finish, retrieves and decodes the result, and lands a clean transcript in ATP, end to end, in one low-code flow. No functions to deploy, no servers to manage, no glue code to maintain. You build it once, visually, in the OIC canvas, and every call from then on transcribes and stores itself.
That is the Voice-to-Service pattern: OIC orchestrates the entire flow using its embedded actions for OCI AI Speech and OCI Object Storage, alongside adapters such as the ATP Database Adapter. Building on the same agentic foundations described in the Agentic AI in Oracle Integration and OIC Knowledge Base blogs, Voice-to-Service shows how a single OIC integration turns raw audio into a living, self-updating knowledge layer for your support organization.
Intelligent Document Processing with AI Agents and Oracle 26ai RAG using Oracle Integration by Ganesh Babu GM, Venkat Chowdhury, Prakash Masand
Introduction:
Every business runs on documents that trigger critical processes and decisions. Yet finding the right information often means hours of manual review. Now multiply that across thousands of documents.
Oracle Integration (OIC) Workflow AI Agents, powered by Retrieval-Augmented Generation (RAG), transform this challenge by understanding business documents, extracting key insights, and orchestrating governed workflows that deliver faster, more accurate, and auditable outcomes.
Business Scenario:
Organizations often manage large volumes of partner and customer contracts that directly impact pricing, incentives, payouts, or revenue-sharing processes. Manually reviewing these agreements is time-consuming, error-prone, and difficult to scale. An AI-driven contract processing solution automates the intake, interpretation, and processing of contract documents. It converts complex agreements into structured, actionable data that downstream teams and systems can use.
• Faster and more accurate payout processing
• Reduced manual review effort and operational errors
• Improved auditability, compliance, and dispute resolution
• A centralized source of truth for Finance, Sales Operations, and partner management teams
Business Challenges:
Traditional automation works well when inputs are predictable. Contracts, however, are usually unstructured and vary by customer, partner, region, and negotiated terms. This creates multiple challenges:
• Key clauses may appear in different sections or formats across contracts.
• Business rules may require contextual interpretation.
Bringing OCI Generative AI Models to Oracle Integration Agentic AI by Steve Tindall
Ever since we released the new Agentic AI features in OIC, I have had many people ask me about the connection OIC uses to LLMs and where the data is processed, and whether or not the data leaves their OCI tenancy. In this blog, I want announce our support for using models securely inside the Oracle cloud and clearly answer these questions.
With the rapid evolution of Agentic AI in Oracle Integration, the focus has been clear: give customers flexibility in how they design, deploy, and govern AI-powered automation.
With the 26.04 release, we’re taking the next step by introducing support for OCI Generative AI models as a first-class option for AI agents in Oracle Integration Cloud (OIC). You can read all about OCI Generative AI in this blog.
This is more than just adding access to a greater number of models. It’s about giving organizations greater control over where AI runs, how data is handled, and how AI aligns with enterprise governance requirements.
Expanding Model Choice for Agentic AI in OIC
Oracle Integration follows a pragmatic AI approach—combining deterministic workflows with generative AI, while maintaining enterprise-grade governance and control.
Oracle Integration 26.07: The Missing Piece in Enterprise AI Isn't the Model—It's the Integration Layer by Jyotiee Insights
Over the past two years, enterprise conversations have been dominated by Large Language Models (LLMs), AI copilots, and generative AI. Organizations have rushed to experiment with intelligent assistants capable of summarizing documents, answering questions, and generating content. While these innovations have captured headlines, many enterprises are discovering a fundamental truth:
AI is only as valuable as the business systems it can access and the workflows it can execute.
An AI assistant that cannot interact with ERP, CRM, HR, procurement, or finance systems remains largely conversational. True enterprise value emerges when AI moves beyond answering questions and begins orchestrating real business processes across connected applications.
This is where Oracle Integration 26.07 becomes strategically significant.
Rather than introducing another AI chatbot or standalone assistant, Oracle has enhanced the integration platform that connects enterprise systems. The latest release adds Agentic AI capabilities, callback support for AI agents, improved knowledge management, human-in-the-loop approval workflows, enhanced Oracle ERP Cloud adapter diagnostics, and new integration recipes.
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