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HCM · ERP · SCM · EPM · PPM · E-Business Suite

Custom AI for Oracle Fusion
legacy enterprise systems

Packaged AI tools rarely fit an enterprise application as it is actually run. We build AI around your systems and prove it on your data before you commit to a full build.

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Home › Data & AI › Custom AI for enterprise applications

Custom AI for Oracle Fusion and legacy enterprise systems

Less talk about AI, more working proofs of concept

At eAppSys, AI is part of how we deliver, not a separate conversation.

Enterprise applications carry years of configuration, custom code, integrations and data that reflect how your organisation actually works. AI that ignores this tends to stall after the demo. We start from your application as it stands, agree one use case and how success will be measured, and build a proof of concept on your own data.

You see what works before deciding what to scale. If the result does not meet the agreed measures, you can adjust the approach or stop.

Where we are building AI now

Our current work covers three kinds of application. Many clients run more than one.

Oracle Fusion Cloud

  • AI across HCM, ERP, SCM, EPM and PPM
  • Agents built on Oracle AI Agent Studio that run inside Fusion
  • Use cases shaped around your configuration, roles and approval flows
  • Delivered alongside our accelerators, including AgentIQ™ and OneAI™

Example: our Data Integrity Auditor & Resolver Agent, built on Oracle AI Agent Studio, is listed on Oracle Marketplace.

Legacy enterprise systems

  • Older ERP platforms, including Oracle E-Business Suite
  • AI that works with the system as it stands, without replatforming first
  • A practical step for organisations not yet ready to move to the cloud

Custom applications

  • Applications built in-house or by a partner
  • AI enabled within the application you already have
  • Works with its data, workflows and controls as they are
  • No rebuild needed just to add AI

You have a custom application. We enable AI in it.

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What clients use it for

Common starting points for a proof of concept. Each is scoped to your application and data.

 

Data quality

Find and resolve inconsistent, duplicate or incomplete records before they affect reporting or processing.

Exception handling

Flag transactions that need attention and suggest the next action, with a person making the decision.

Document processing

Read invoices, contracts and forms and pass structured data into the application.

Questions in plain English

Let users ask about their data without building a new report each time.

Support and service desk

Triage tickets, suggest fixes from past resolutions and route work to the right team.

Process steps

Take on repetitive steps in finance, HR and supply chain processes, within your existing controls.

How a proof of concept runs

The same five steps for Oracle Fusion and legacy systems.

01

Agree the use case

One problem, a clear scope and the measures that will decide success.

02

Prepare the data

Agree access and data handling, then prepare a representative data set.

03

Build and test

Build the solution against your application and test it on your data.

04

Review the results

Walk through the results with your team against the agreed measures.

05

Decide

Scale it, adjust it or stop. There is no obligation to proceed.

Built within your controls

AI in an enterprise application has to meet the same standards as the application itself.

  • Data handling agreed before work starts, with data kept in your environment where possible
  • Work carried out in line with UK GDPR and your own security policies
  • Role-based access that follows your existing permissions
  • A person approves decisions that matter

Sectors we work in

  • Airlines
  • Banking and financial services
  • Construction
  • Councils
  • Food
  • Health
  • Logistics
  • Oil & Gas
  • Pharma
  • Professional services
  • Public sector
  • Transportation
  • Universities
Common Questions

Frequently Asked Questions

What is a proof of concept for AI?
A small, time-boxed build that tests one AI use case on your own data against success measures agreed at the start. You see the result before deciding whether to build further.
No. We currently build custom AI for Oracle Fusion Cloud, for legacy enterprise systems such as older ERP platforms, and for custom applications built in-house or by a partner.
Not always. Many use cases can run alongside an existing system. The proof of concept shows what is possible with the system as it stands.
We agree data handling before any work starts. Where possible, data stays within your environment, and all work follows UK GDPR and your own security policies.
We review the findings with you and you decide whether to adjust the approach or stop. There is no obligation to proceed to a full build.
Yes. Client references are available on request.
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