Tested on your records
Every field runs on real sample records before you can approve. A bad date shows up here, not in a failed import at 2 a.m.
Move data into Oracle Fusion. Proven before it runs.
IntoMatix connects Salesforce and files to Oracle Fusion. AI drafts the mapping, every field is tested on your own records, and you approve it in plain English.
SalesforceAccount
Account Name
Billing Country
Customer Since
Credit Limit
Currency
Status
Oracle FusionCustomer
Party namewaiting
Credit limitwaiting
Countrywaiting
Currencywaiting
Account establishedwaiting
Statuswaiting
Testing each field on 10 recent Salesforce accountsApprove in the demo
ConnectsSalesforceCSV and PDF files over SFTPOracle Fusion Cloud ERP
Every field tested on your records before go‑live.
Plain English, not code
Consultants review what a field does, not how it is written.
Failures come with fixes
Only the bad rows are held back. Each one says what happened and how to fix it.
Ready for every Fusion update
Oracle updates Fusion four times a year. Point a flow at your test pod, draft again, and every field is tested on real records before you approve.
Your data stays yours
The AI sees field names and value shapes, never your record values.
14 of 20 fields, no AI needed
Rules match most fields without AI. The AI only handles the rest, which keeps every flow fast and predictable.
From two systems to a tested flow in three steps.
- 1
Connect
Sign in to Salesforce and Oracle Fusion, or point at an SFTP folder. IntoMatix reads the fields on both sides and ten recent records.
- 2
Review
Rules match most fields in seconds and the AI drafts the rest. Every field is tested on your records and written in plain English.
- 3
Approve and run
Pick a schedule and approve. A record that fails is held back with the reason and a fix. Everything else keeps loading.
Integration the usual way
- Weeks of developer time on a mapper canvas
- Errors show up as a failed import after go-live
- One bad row and the whole file is rejected
- Every quarterly Oracle update is a gamble
- Nobody can tell which flows are healthy until someone complains
With IntoMatix
- A finished mapping to review in an afternoon, for a typical flow
- Every field tested on your records before approval
- Only the bad rows are held back, each with a fix
- Draft again on your test pod before each Fusion update
- One home screen showing every flow, run and system
See it work.
The same screens your team uses, running on sample data. Click through the four stages of a flow.
AI drafts every field
Rules and AI propose a source for all 20 Fusion fields, in plain English. Only the doubtful ones ask for a human.
Map Account to Customer20 fields, 3 need a look
Party nameAccount Name, trimmedRule
Country (ISO code)Billing Country through the countries lookupAI
Customer classIndustry through the industry_class lookup, else "OTHER"
Credit limitCredit Limit (text) as a number
Account establishedCustomer Since as a dateAI
Salesperson emailOwner Email in lower case
StatusStatus through the status lookupAI
Why IntoMatix.
Teams moving data into Oracle Fusion usually weigh three routes. Here is what each one asks of you.
QuestionSpreadsheets and file uploadsA general integration platformIntoMatix
Who builds the mappingA consultant, by hand, in a spreadsheetA developer, field by field on a canvasRules and AI draft it. Your consultant reviews and approves it.
When mistakes show upWhen Fusion rejects the uploadIn testing, or after go-liveBefore approval, tested on your own records
What one bad record doesOften stops the whole fileDepends on the error handling someone builtHeld back with the reason and a fix. The rest load.
Fixing itCorrect the file and upload it againA developer change and a redeployAdd the value to a lookup and retry the held records
Who can read the mappingWhoever made the spreadsheetPeople trained on the toolAnyone. Every field reads in plain English.
Built aroundAny systemAny system, so the Fusion details are yours to learnOracle Fusion: its fields, its codes, its REST resources
Your records stay yours
The AI sees field names and the shape of values, such as “####-##-##” for a date. Never the values themselves.
A person approves every mapping
Each approval is a saved version with the approver's name, so you always know what ran and who signed off.
Running twice never duplicates
Records are matched on a key you choose, so a re-run or a retry updates instead of creating copies.
Watch a mapping get proven.
The demo runs on sample data for a fictional company. Apply the AI fix, confirm three fields and approve.
Open the live demo