Oracle's Fusion Agentic Applications, launched in March 2026, split large language model (LLM) reasoning from deterministic enterprise calculations. This hybrid approach aims to enhance accuracy and reduce costs for enterprise AI agents.
TL;DR
- Oracle's Fusion Agentic Applications use a hybrid architecture, separating LLM reasoning from deterministic enterprise calculations.
- This approach aims to improve accuracy and reduce costs for enterprise AI agents.
- The applications are designed to operate within existing Oracle Fusion Cloud Applications, ensuring governance and compliance.
What happened
Oracle's Fusion Agentic Applications were launched at Oracle AI World in London in March 2026. The platform includes 22 initial applications spanning finance, human resources, supply chain, and customer experience.
In July 2026, Oracle expanded the platform with a new AI-native builder experience, allowing customers and partners to create their own Fusion Agentic Applications.
The hybrid architecture separates LLM reasoning from deterministic enterprise calculations, ensuring accurate and cost-effective enterprise AI agents.
Why it matters
This hybrid approach addresses the intrinsic nondeterminism and high cost of LLM inference for enterprise-scale computations.
By assigning LLM inference only to reasoning tasks, Oracle's applications ensure accurate and auditable results for critical enterprise processes.
The architecture is designed to comply with regulatory requirements, such as the EU AI Act, making it a suitable choice for European deployments.
Key facts
- Oracle's Fusion Agentic Applications were launched in March 2026 with 22 initial applications.
- The platform was expanded in July 2026 with a new AI-native builder experience.
- The hybrid architecture separates LLM reasoning from deterministic enterprise calculations.
- Oracle's applications are designed to operate within existing Oracle Fusion Cloud Applications.
- The architecture ensures accurate and auditable results for critical enterprise processes.
- Oracle's cloud applications revenue grew 10% year over year to $4.2 billion in Q1 fiscal year 2027.
- The applications are designed to run at configurable autonomy levels.
- The architecture is positioned to satisfy EU AI Act requirements structurally.
Context
Enterprise AI agents are designed to autonomously perform tasks within a business, but ensuring their actions are accurate, auditable, and cost-effective remains a challenge.
Oracle's hybrid approach addresses these challenges by separating LLM reasoning from deterministic enterprise calculations, ensuring accurate and cost-effective enterprise AI agents.
This approach is particularly relevant in the context of regulatory requirements, such as the EU AI Act, which mandates conformity assessment, human oversight, and transparency for certain AI-driven enterprise decision-making processes.