The eight steps below represent the actual sequence the Oracle AI platform executes for every incident. We use ORA-01652, a TEMP tablespace exhaustion error, as the concrete example throughout.
ORA-01652 fires when Oracle cannot extend a temporary segment because the TEMP tablespace has run out of space. In an AP environment, this surfaces as invoices stuck in INCOMPLETE status — blocking payment processing, GL transfer, and period close. The platform handles the entire resolution sequence from alert to fix.
The complete 8-step sequence at a glance. Scroll down for the full technical detail of each step.
A user submits "Invoices stuck in status INCOMPLETE with ORA-01652" through the Oracle AI support portal. The portal captures the error code, module, description, and Oracle environment version as a structured JSON payload sent to an n8n webhook listener.
{
"error_code": "ORA-01652",
"module": "AP",
"description": "Invoices stuck in INCOMPLETE status",
"environment": "EBS R12.2.10",
"priority": "HIGH"
}The n8n webhook receives the JSON payload and passes it to an LLM-based router agent. The agent evaluates the error code, module, and description to classify the incident domain — in this case, a DBA-level tablespace issue — and dispatches the correct diagnostic workflow branch. Classification determines which diagnostic scripts run, which Oracle Support search terms are used, and which approval tier applies to the fix.
n8n triggers the Tablespace Diagnostic Script from the 65-script library at scripts.williamagreen.com. The script executes via the n8n OracleDB node using JDBC, running structured SQL checks against the live database and returning results as normalized JSON for LLM analysis.
SELECT tablespace_name,
used_percent,
bytes_used,
bytes_free
FROM dba_tablespace_usage_metrics
WHERE tablespace_name = 'TEMP';The structured diagnostic output is passed to the LLM analysis engine. The model identifies root cause based on specific patterns in the script output, and also consults the RAG knowledge base for prior resolutions matching this error code and environment.
Tablespace: TEMP | Used: 99.8% | Free: 40MB
Root cause: TEMP tablespace exhaustion.
50 AP invoices cannot complete sort operations.
Resolution: Extend TEMP by 5GB minimum.The Playwright browser agent activates using a pre-authenticated session stored in auth.json, navigates to My Oracle Support, searches "ORA-01652 TEMP Tablespace EBS R12", and extracts the Symptoms, Cause, and Solution sections from the top-ranked article. This retrieval runs in parallel with Step 4.
Because extending a tablespace requires an ALTER SYSTEM command — a High-Risk DDL-level action — the platform executes its Safe-Stop sequence. n8n serializes the full proposed fix context and sends a Decision Tower notification to the lead DBA via Slack. The notification presents three panels of evidence: the problem, the AI reasoning path, and the dry-run result. The DBA sees Approve, Reject, and Edit SQL buttons directly in the Slack message.
The Decision Tower notification as it appears in Slack — three evidence panels and three action buttons. The DBA's entire involvement is reviewing this card and clicking one button.
Upon DBA approval, n8n validates the JWT authorization token and executes the fix via the OracleDB node using the exact SQL that was shown in the approval notification — no substitution, no modification. A signed audit record is written immediately after execution, capturing agent identity, approver identity, exact SQL run, and the before/after tablespace state.
ALTER DATABASE
TEMPFILE '/oracle/oradata/temp01.dbf'
RESIZE 10240M;The complete resolution package — diagnostic output, root cause analysis, Oracle Support Note reference, fix applied, DBA approval record, and verification result — is vectorized and stored in Milvus with enriched metadata. The next ORA-01652 incident in this environment retrieves this resolution immediately, reducing diagnosis time to near zero.
For High-Risk fixes, the DBA reviews the AI reasoning before approving any action. The Decision Tower UI shows exactly what evidence the AI used and what SQL it proposes to run. A misidentified root cause results in a Reject decision — not an erroneous fix. For Low-Risk diagnostic actions, a wrong analysis produces a wrong report, which the user can flag to trigger a re-run.
Yes. For Oracle EBS R12.x, the platform connects via JDBC and SQL*Plus for direct database diagnostics. For Oracle Fusion Cloud, the platform uses Fusion REST APIs, OTBI logical SQL, BIP data models, and ESS job history endpoints — the same access methods documented across the 15 Fusion-specific scripts at scripts.williamagreen.com.
n8n is self-hosted via Docker, deployed within or connected to the corporate network that reaches the Oracle EBS instances. The Playwright browser agent runs in a separate container. Oracle credentials are stored in n8n's encrypted credential vault or HashiCorp Vault — never hardcoded in any script or workflow definition.
The diagnostic script foundation covers 11 Oracle modules: Accounts Payable, Accounts Receivable, General Ledger, Fixed Assets, Purchasing, Inventory, Order Management, WIP/Manufacturing, Project Accounting, HCM/Payroll, and System/Technical. All 65 scripts are documented at scripts.williamagreen.com.
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