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' VBScript — Common workflow patterns Dim doc = app.Core.GetDocumentByID(docID) doc.AddToHistory("Processed by import") Dim remaining = objApplication.BatchDocumentsRemaining objApplication.PropertyBag.SetProperty("Status", "Complete") objApplication.PropertyBag.Clear
// C# Unity API — OnBase 25.1 compliant Document doc = app.Core.GetDocumentByID(docID); app.Core.LogManagement.CreateDocumentHistoryItem(doc, "Processed by import"); int remaining = wfArgs.BatchDocumentsRemaining; wfArgs.SessionPropertyBag.Set("Status", "Complete"); // SessionPropertyBag persists across batch — no .Clear needed
' VBScript — Keyword creation & error handling Set RegString = New regexp If RegString.Test(emailValue) Then IsValid = "Y" keyType.CreateKeyword(keywordValue) If err.Number <> 0 Then Err.Raise vbObjectError, , "Keyword failed" End If
// C# Unity API — Safe patterns bool isValid = Regex.IsMatch(emailValue, pattern, RegexOptions.Compiled, TimeSpan.FromSeconds(1)); if (!keyType.TryCreateKeyword(keywordValue, out var keyword)) throw new DatabankException( $"Unable to create keyword [{keywordName}]");
' VBScript — Document locking & autofill Dim docLock = doc.LockDocument() mod.ApplyChanges() docLock.Release() Call results.BeginRow() Call results.AddData("Email", primaryValue) Call results.EndRow() pdfType = app.Core.FileTypes.Find(16)
// C# Unity API — Resource discipline using (DocumentLock docLock = doc.LockDocument()) { mod.ApplyChanges(); } // lock auto-released var row = afArgs.Results.CreateExternalAutofillKeysetData(); row.SetKeyword(CreateKeyword("Email", primaryValue)); afArgs.Results.AddExternalKeywordAutofillKeysetData(row); const int PDF_FILE_TYPE_ID = 16; pdfType = app.Core.FileTypes.Find(PDF_FILE_TYPE_ID);
.doc, .docx, .txt, .md, .png, .jpg, .jpeg · Max 20 MB per file, 10 files per run Five AI systems running in parallel so you can just ask a question.
RAG-grounded search across 8 curated hubs: version-specific Module Reference Guides (22.1 through 25.1 + legacy), Release Notes, Development SDK, and DataBank Standards. Auto-selects the right hub based on your role and version.
AI-powered semantic search across multiple data sources: cases, emails, comments, SCRs (known defects), KB articles, and case notes. Data synced regularly from Salesforce.
Multiple AI models working together. Fast models handle intent classification, search term extraction, and draft customer responses. Advanced models handle synthesis: merging documentation + case data + live Salesforce into a single grounded answer.
Paste a case number or Salesforce URL and the pipeline pulls live case details, related SCRs, KB articles, case notes, and account history directly from Salesforce. Version is auto-detected from the case record.
Every case, email, SCR, and KB article is converted to a high-dimensional vector for semantic search. Hybrid search combines semantic similarity with keyword matching for fast, relevant results.
Automated workflows keep data current by syncing case data, SCRs, KB articles, and notes from Salesforce, then generating search vectors. Runs on a regular schedule.
All queries processed under enterprise data agreements (Box, Anthropic, OpenAI). No data is used for model training. MFA-secured with row-level database security.