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Oracle launches an enhanced AI Agent Studio for its Fusion Applications, unveiling a marketplace of partner-built AI agents, expanded LLM support, and advanced workflow tools to accelerate enterprise AI adoption.
Oracle has unveiled significant enhancements to its AI Agent Studio for Fusion Applications, introducing the Oracle Fusion Applications AI Agent Marketplace alongside expanded support for major large language models (LLMs) and advanced AI development tools. This new marketplace opens up access to Oracle-validated, partner-built AI agents seamlessly integrated within Oracle Fusion Applications, designed to help businesses automate workflows and tackle industry-specific challenges without disrupting existing processes.
The AI Agent Marketplace offers a curated selection of partner templates available directly through the Oracle AI Agent Studio. Users can conveniently install, test, and manage both Oracle-certified partner agents and Oracle’s own pre-built agents from a single unified platform. This ecosystem features contributions from an extensive range of system integrators and independent software vendors, including prominent names from the Oracle PartnerNetwork such as Apex IT, Grant Thornton, Huron, IBM Consulting, and Infosys. Furthermore, global consulting firms like Accenture, Deloitte, KPMG, and PwC provide additional agent templates exclusively for their joint customers, broadening the marketplace’s comprehensive industry reach.
Notable examples of practical AI applications within the marketplace include IBM’s Smart Sales Order Entry Assistant, which utilises natural language prompts to streamline the sales order process by reducing errors and cutting down manual tasks, thereby improving customer satisfaction. Similarly, KPMG’s Purchase Order Item Price History agent offers procurement teams quick access to historical order data—such as previous suppliers, purchase dates, and average prices—facilitating better negotiation and decision-making.
The updates to Oracle’s AI Agent Studio also introduce enhanced agent management and workflow capabilities. New features include centralized prompt libraries and lifecycle management tools that store and organise agent prompts and use cases to improve consistency and efficiency. The studio’s topics management functionality enhances governance by defining prompt boundaries for agents operating in overlapping domains. Additionally, the platform now supports retrieval-augmented generation (RAG), allowing AI agents to incorporate and analyse diverse data formats—from documents and images to tables—and access external content repositories like SharePoint. This broadens the agents’ data retrieval and contextual response abilities significantly.
Workflow capabilities have been further refined, enabling users to establish deterministic execution for mission-critical processes, chain multiple agent workflows for complex task handling, embed agent nodes within broader workflows, and incorporate human-in-the-loop controls for enhanced oversight. These additions underscore Oracle’s commitment to delivering comprehensive automation solutions that blend AI efficiency with necessary human judgement.
Adding to this, Oracle has expanded support for a broader array of LLM providers, including OpenAI, Anthropic, Cohere, Google, Meta, and xAI. This multi-model integration offers customers flexibility in selecting the models best suited to their unique business needs. According to Natalia Rachelson, Group Vice President of Cloud Applications Development at Oracle, the company benefits from a distinctive market position by owning the technology infrastructure underpinning their entire stack. Oracle Cloud Infrastructure (OCI), purpose-built for AI, facilitates direct and optimised access to these LLMs. Rachelson explained in an interview with TechDay that this direct access enables Oracle’s engineering teams to tune and collaborate with the models efficiently, removing the typical bottlenecks of token limitations and integration delays.
Oracle’s approach contrasts with competitors that often rely on acquisitions to build out AI capabilities. Instead, Oracle has natively embedded AI capabilities within Fusion Applications, eliminating the complexity of stitching together disparate technologies. New technical features also include Model Context Protocol (MCP) integration to enhance agent connectivity with external systems, cross-agent collaboration through A2A agent cards, and a secure credential store for managing authentication details across APIs and third-party services.
The platform’s observability has been boosted with a comprehensive monitoring dashboard that enables real-time agent performance reviews, systematic evaluations, workflow analysis, and troubleshooting. Importantly, token usage monitoring allows customers to manage costs associated with premium LLM utilization, reflecting Oracle’s attention to practical operational concerns.
Oracle emphasises that these AI agents, developed within the AI Agent Studio, are embedded into the world’s most complete suite of cloud applications and run natively on Oracle Cloud Infrastructure with advanced security measures—all at no additional cost. This positions Oracle Fusion Applications as a compelling solution for enterprises seeking to accelerate AI adoption at scale securely and efficiently.
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Source: Noah Wire Services
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