Legacy Client-Server → Salesforce SaaS

Link legacy database and Salesforce org via the connection library.

Auto-catalogue tables, fields, relationships, and ERD diagram. For IDOX Uniform migrations, use the DB Schema Scraper (Oracle metadata extraction) or PDF Documentation Scraper to import schema directly.

Use the Field Extractor bookmarklet to capture form fields from intranet/local UI pages. Cross-references with live database columns, verifies tables via URL parameters, and flags bad screenshots with alternative record suggestions. ⭐ Add candidate record pairs — matched source↔destination data — for reverse-engineering with 95%+ confidence.

PII detection, cardinality, null rates, quality scores, AI analysis.

Pull picklists, validations, triggers, and record types from Salesforce.

Copy schema and data (including Salesforce data) to Postgres staging so the mapping engine can analyse real records. SSL-encrypted connections; PII fields protected with AES-256-GCM or SHA-256. One of three prerequisites for the Screen Grab → Mapper pipeline.

With all three prerequisites staged (PII analysis, Screen Grab data, Postgres data), the engine generates confidence-scored field mappings in minutes. The non-AI reverse-engineering engine is the default (zero data shared with any AI provider); the AI engine is admin-gated (off by default). Cross-references UI field labels against database columns, applies PII flags, maps code/value pairs to SF picklists. ⭐ Supply candidate record pairs for 95%+ confidence via value-matching — without them, falls back to name-matching (70-80%).

Validation AI Assistant checks field mappings against live Salesforce required fields, picklists, validation rules, and data types at design time — with accept/reject resolutions that persist. Risk log with Kanban board for visual drag-and-drop tracking, sign-off dashboard. Merge Review compares existing mappings against new AI-generated versions — accept or decline per-diff. Tag and filter mappers by category. Reviewers can override per-mapping AI confidence scores with timestamps and notes.

Copy complete schema and all data — including documents and notes — to Postgres staging area for loading. Use the SQL Server Utilities (File Exporter for binary/file columns, RTF Extractor for Rich Text content) to extract files and RTF data from the source database before staging. Documents and notes are staged here so they can be re-linked to new Salesforce records after the full load.

Table loader, 2-pass schema loader, document/note loaders. Schedule unattended Postgres → Salesforce loads that run overnight — with pre-load SF metadata toggle (validation rules, triggers, flows) and admin failure email alerts.

Percentage subset load with dependency-aware snapshots.

2-pass: insert parents, resolve lookups, write back DT_IDs. Or schedule the entire data transfer to run end-to-end overnight unattended — source refresh → transformations → Salesforce load — with SF metadata toggle, failure review, and admin email alerts. See the Unattended Pipeline guide.

Documents and notes re-linked to new SF records.

Full audit trail, sync logs, backup/restore safety net. Merge history dialog shows all past merge reviews per mapping. Generate a Client Management Report (PDF) from each mapping — cover page, field definitions with screenshot markers, Data Profiler results, landscape mappings table with per-mapping confidence and AI reasoning, SQL joins, validation rules, and AI Insights.