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From "assistant" to autonomous.

Oracle AI agents are built directly into Oracle Fusion Cloud — leveraging your business data to deliver answers that aren't just smart, but contextually accurate to your organization. They reason, recommend and execute on behalf of your teams.

Why Oracle AI agents

Context-aware, autonomous business intelligence.

Seamlessly Embedded

Not bolt-on AI — agents live inside the apps your team already uses, so adoption is rapid with minimal training.

Cognitive Reasoning

They don't just search; they think through logic to answer complex questions and execute multi-step tasks.

Universal Specialization

Tailored roles across Finance, HR and Procurement — streamlining audits, onboarding and vendor workflows.

Enterprise-Grade Security

Data stays within Oracle Cloud — timely and relevant never compromises safe and private.

Ready from day one

Author. Answer. Action.

Authoring

Create & summarize.

Drafts emails, crafts reports and summarizes long documents — saving hours and ensuring consistency.

Answering

Guide & inform.

Instant, accurate answers from real-time business data — a single source of truth, no search time.

Actioning

Execute & automate.

Plans and completes multi-step tasks across tools — complex workflows without human intervention.

Delivery lifecycle

A 7-step framework for faster ROI.

Phase 1 · Strategy & Design
1

Identify use cases

Pick high-impact areas where AI solves real bottlenecks.

2

Map logic

Design the workflow as if training a human expert.

Phase 2 · Build & Launch
3

Source

Start fast with Oracle prebuilt templates.

4

Build

Develop custom tools and agents.

5

Verify

Rigorously test every scenario.

Phase 3 · Optimize & Grow
6

Launch

Managed rollout for high adoption.

7

Refine

Use feedback to improve accuracy and cut cost.

The case for agents

Human-led vs agent-driven analytics.

DimensionHuman-LedAI Agent–Driven
Data Processing Time4–48 hrs / cycle<1–5 min (real-time)
Decision Latency1–3 business daysSeconds to minutes
Analyst Productivity1 analyst : 3–5 stakeholders1 agent : 100+ users
Insight Coverage60–70% of data95–100% utilization
Error Rate5–10%<1%
Cost per Insight$40–120 / report$1–5 / insight
Availability~2,000 hrs/yr8,760 hrs/yr (24/7)
Time to Deploy8–16 weeks1–3 weeks (templates)
ROI Timeline12–24 months3–6 months
UAE MarketWithout AgentsWith Agents
Operational Cost100% baseline25–40% reduction
Decision Cycle Time2–5 days<1 hour
Customer Response4–24 hours<1 minute
CSAT70–78%88–95%
Process Automation20–35%70–90%
Annual OPEX Growth8–12%2–4%
Time to Scale6–12 monthsDays to weeks
UAE AI Strategy 2031 AlignmentPartialStrong / Direct
EBITDA ImpactNeutral to negative+5–15% uplift
Showcase · GITEX

Intelligent Banking Assistant.

An AI-powered financial-advisor chatbot for young professionals, leveraging agentic and generative AI for real-time, personalized guidance on budgeting, spending, investments and planning — turning complex money matters into simple, actionable insight.

Real-Time Monitoring

Tracks spending and income instantly, alerting on patterns like dining or shopping overspend.

Personalized Recommendations

Custom budget, savings and investment suggestions tied to individual goals.

Scenario Simulations

Test what-ifs — a salary raise's impact on savings, or a big purchase on cash flow.

Investment Guidance

Beginner-friendly advice on low-risk options with clear growth projections.

Personalized & Agentic

Proactively adjusts and initiates — nudging when spend exceeds limits or after high expenses.

Dashboard Integration

Visual dashboards for savings, spending trends and plan progress.

AI architecture

How a query flows through the stack.

APEX → Oracle Digital Assistant → REST → Autonomous Database (with OML) → LLM on OCI, and back as a natural-language response.

APEX + ODA Web SDK
Hosts the chatbotQuery submission & display
Oracle Digital Assistant
Intent detectionRoutes to REST APIIntegrated LLM for NLP
REST Integration Layer
Secure data retrievalBridges ODA & database
Autonomous DB (ATP)
Stores transactional dataResponds to REST queries
Oracle Machine Learning
Embedded in ATPPredictions & classification
Large Language Model (OCI)
Receives query + ATP dataGenerates natural-language response
Where agentic AI adds value

Built for real-life change.

  • Real-time responsiveness — autonomous monitoring and notifications give instant feedback.
  • Personalization — proactive recommendations and simulations tied to live data.
  • Reduced effort — the interaction agent handles complex queries autonomously.
  • Scalability — auto-scales on OCI to handle demo-day and production traffic alike.
Customer story · "Rashid"

First steps into investment.

Ahmed, a 25-year-old IT specialist in Abu Dhabi, is intimidated by investing. The assistant assesses his risk tolerance, explains the Rule of 72, suggests low-risk UAE options like ETFs or sukuk, and simulates portfolios — "Start with AED 2,000/month — projected AED 120,000 in 5 years."

Higher wealth accumulation
Increased confidence
Same savings behavior
Long-term habit formation

Deploy agents that act, not just answer.

From a single high-impact use case to an enterprise-wide rollout on Oracle Cloud.