AI-POWERED · ENTERPRISE READY · SQL SERVER & POSTGRES

Database Migration, Reimagined with AI

Cygenix connects to SQL Server, Azure SQL, Postgres and file sources (CSV, Excel, text) — on-premises or in any cloud. It maps your schema intelligently using Claude AI, validates results, and delivers professional reports — in minutes, not months.

Register interest → See the platform
AI
COLUMN MAPPING
Any
VALIDATION SOURCE
Azure
MANAGED IDENTITY
100%
BROWSER-BASED
🟢 Connected · Source DB · 342 tables loaded
✓ AI mapped 47 columns in 2.3s
🎨 Visual mapper · 47 connections drawn
📊 Validation scripts loaded · 3 sources
📦 Execution plan · 4 groups · 27 jobs
🟢 Migration complete · 0 errors
🔄 Was/Is rules applied · 312 translations
🏷 @@StartDate substituted · 14 SQL files
📅 Project Plan updated · 7 days to completion
🔗 Jira sync · 23 tasks imported
📄 Conversion report exported · Excel ready
⚡ Performance tuned · 5,000 rows/page · 4 threads
🟢 Connected · Source DB · 342 tables loaded
✓ AI mapped 47 columns in 2.3s
🎨 Visual mapper · 47 connections drawn
📊 Validation scripts loaded · 3 sources
📦 Execution plan · 4 groups · 27 jobs
🟢 Migration complete · 0 errors
🔄 Was/Is rules applied · 312 translations
🏷 @@StartDate substituted · 14 SQL files
📅 Project Plan updated · 7 days to completion
🔗 Jira sync · 23 tasks imported
📄 Conversion report exported · Excel ready
⚡ Performance tuned · 5,000 rows/page · 4 threads
Platform Features
Everything you need to
migrate with confidence
🔌
Live Database Connection
Connect directly via standard connection strings to SQL Server (on-prem, Azure SQL, Azure Managed Instance, AWS RDS, Google Cloud SQL) and PostgreSQL (self-hosted, RDS, Aurora, Azure Database, Cloud SQL, Supabase, Neon). Azure Function with Managed Identity also supported.
📁
File Import as a Source
Drop a .csv, .xlsx, .tsv or .txt file to use as a source for mapping and migration. Multi-sheet Excel workbooks handled; map columns to target schema like any other source.
🔀
Cross-Engine Migration
Migrate between different database engines — Postgres to SQL Server, SQL Server to Postgres. Built-in DDL generator creates target tables from the source schema with opinionated type mappings and clear warnings for lossy conversions (jsonb, arrays, hierarchyid and similar).
🤖
AI Column Mapping
Claude AI automatically maps columns between source and target schemas. Target-driven layout shows every target column with a source dropdown, fixed value override and truncation warnings.
🎨
Visual Drag-and-Drop Mapping
See the whole schema at once. Source columns left, target columns right, connection lines fanning across — colour-coded by AI confidence. Drag to map, click a line to remove, tap Fullscreen for complex jobs.
🔄
Was/Is Value Translation
Upload translation tables to automatically convert values during migration — status codes, lookup IDs, department names, currency codes, and more.
✅
Flexible Validation
Add any table as a validation source. Pick which column holds the SQL, choose which columns appear in the report. Run any number of validation tables against any database.
📦
Grouped Execution Plans
Organise jobs the way an enterprise migration actually runs — group by concern (Static Config, Masters, Transactions), drag jobs between groups, pick sequential or parallel per group. Tick-box selection runs only what you need.
🏷
System Parameters
Define @@Tokens once, use them everywhere. Values get substituted across SQL, Wasis rules, WHERE clauses, literal mappings and custom jobs at runtime. CSV / JSON import and export, filter and sort.
📊
Professional Reports
Export client-ready Excel reports with summary, migration results, column mapping, Was/Is rules applied, and execution logs — ready to hand to stakeholders.
📅
Project Planner
Full calendar (year/month/week/day views), task tracking, blocker management, execution phase tracker, and activity log — driven by your project completion date.
🔗
Jira & Smartsheet Sync
Your migration plan doesn't live in a silo. Bidirectional sync between Cygenix tasks and Atlassian Jira or Smartsheet — import existing issues, push new tasks, map your own fields. Credentials stay in your browser.
⚡
Performance Tuning
Configure fetch page size, insert batch size, concurrency, timeouts and retry behaviour. Quick presets for Small DB, Large DB, Azure SQL and Cautious mode.
💻
SQL Editor
Full-featured SQL editor with script library, connection selector, find & replace, results grid, history, AI assistant, and one-to-many mapper for complex transformations.
🧽
Data Cleansing
Strip PII, redact sensitive fields, deduplicate rows, standardise formats and anonymise test data before migration. Pick columns, choose per-column strategy (mask, hash, null, randomise), preview rows, then apply.
Intelligent Column Mapping
Target-driven mapping
with AI confidence
Every target column shown as a fixed row. Source column, fixed value override, truncation warnings and AI confidence — all in one place.
Simple Map
One table to one table, mapped in seconds
Select source and target tables. Claude AI maps every column automatically. Override any row, add a fixed SQL value, hide unmapped columns, filter by match confidence.
  • Target-driven layout — every target column shown, source is a dropdown
  • ✦ Visual mode — drag-and-drop pill view with connection lines and fullscreen
  • Fixed value column — type any SQL literal (N'Value', NULL, GETDATE())
  • ⚠ Truncation warnings when source char type is wider than target
  • 👁 Show/Hide Unmapped toggle to focus on what matters
  • AI uses Haiku with automatic retry on overload
Object Mapping · Simple Map
👁 Hide Unmapped
Source col
Src type
Target col ▲
Fixed value
Match
✓ 15 columns mapped · 2 hidden (unmapped)
INSERT INTO [TargetDB].[dbo].[effective_dated_records]
SELECT [run_number], [code], LEFT([description_text], 100), N'Enterprise', [active_flag]
FROM [SourceDB].[dbo].[effective_dated_records]
Visual Mapping
See the whole schema at once
Switch from the table view to a drag-and-drop pill view. Source columns left, target columns right, connection lines fanning across — colour-coded by AI confidence. Fullscreen mode expands the canvas to your full window for complex jobs.
  • Drag any source pill onto a target to create the mapping
  • Bezier connection lines redraw on every scroll and resize
  • Click a line (or the ✕ on a target pill) to remove the mapping
  • Green / amber / red / grey pills — HIGH / MEDIUM / LOW / unmapped
  • ⛶ Fullscreen toggle expands to the full browser window; Esc to exit
  • Bidirectional state sync with the Table view — switch any time
👉 Try it — drag a source pill onto a target, or click a line to remove it
Object Mapping · Visual view
⛶ Fullscreen
5 mapped · drag to add more
One-to-Many Map
One source, multiple target tables
Map a single source table into multiple target tables in one operation. Each target card has its own AI mapping, filter, hide-unmapped toggle, FK relationships and fixed values.
  • Add as many target table cards as needed
  • PK mode per card — Identity, GUID or natural key
  • FK columns reference PK variables from parent cards
  • AI maps each card independently with overload retry
  • Single generated SQL script covers all target tables
Object Mapping · One-to-Many · 3 target tables
dbo.ClientMaster 5 mapped 🤖 AI map 👁 Hide Unmapped
PK: Identity · @ClientID · 5 cols mapped
dbo.ClientAddress 4 mapped 🤖 AI map
PK: GUID · FK → @ClientID
dbo.ClientContact 3 mapped 🤖 AI map
PK: Identity · FK → @ClientID
Flexible Validation
Any table. Any SQL. Any database.
No longer locked to a fixed schema or table name. Add any table as a validation source, pick which column holds the SQL to execute, choose which columns appear in the failure report, and run against any database.
  • Add multiple validation tables from different connections
  • Pick the SQL column, name column and report columns per source
  • Run all, run selected (checkboxes), or run one source at a time
  • Inline result rows shown with your chosen report columns
  • Export to Excel — summary + one sheet per failed script
  • ⏹ Stop mid-run at any time
Data Validation · 3 sources
Post-migration checks
Table: dbo.PostMigrationChecks · SQL col: CheckSQL · 24 scripts
3 fail 21 pass
GL Integrity checks
Table: dbo.GLIntegrityChecks · SQL col: CheckQuery · 8 scripts
8 pass
✓ Pass: 0 ✕ Fail: 0 ⏳ Pending: 0
Project Plan · Calendar — April 2026
Year
Month
Week
Day
◀ April 2026 ▶
M
T
W
T
F
S
S
7
days left
12
done
3
in progress
1
blocker
Project Planner
Plan, track and deliver your migration
A full project management tool built into Cygenix. Calendar views, task tracking, blockers, phase progress and activity log — all driven by your project completion date from Project Settings.
  • Year / Month / Week / Day calendar views — click to add events
  • Outlook-style event modal with type, time, location, attendees
  • Task table with status, priority, phase, owner and due date
  • Blocker management with impact level and resolution tracking
  • 7-stage execution phase tracker — click to set current phase
  • 🔗 Jira & Smartsheet sync — bidirectional, field-mapped, full sync history
  • Activity log records every change automatically
SQL Editor
Full-featured SQL workspace
Write, save, run and manage SQL scripts against source or target databases. AI assistant, find & replace, history, results grid with pivot view and Excel export.
  • Script library — save, name and load any number of scripts
  • Ctrl+Enter to run, Ctrl+F to find, Ctrl+/ to comment selection
  • Results grid with row / pivot view and Excel export
  • Query history with re-load and timestamp
  • AI assistant — describe what you need, Claude writes the SQL
  • Snippet toolbar — SELECT, WHERE, INSERT, UPDATE, TRAN
SQL Editor · Source DB
-- Count records by status for reconciliation
SELECT
  [status_code],
  COUNT(*) AS record_count,
  SUM([amount]) AS total_amount
FROM [dbo].[transactions]
WHERE [created_date] >= '2024-01-01'
  AND [active_flag] = 1
GROUP BY [status_code]
ORDER BY record_count DESC
▶ Run (Ctrl+Enter) |🔍 Find|⬇ Export
status_code
record_count
total_amount
ACTIVE
1,842
£2,341,990
PENDING
234
£89,450
CLOSED
89
£12,100
✓ 3 rows · 12ms
Performance Tuning
Tuned for your environment
Quick presets for common scenarios. Fine-tune batch sizes, timeouts, concurrency and data loading to match your server's capacity. Import and export settings as JSON.
Small DB
1,000 rows/page
1 thread
Full verify
Medium DB
2,000 rows/page
2 threads
Balanced
Large DB
5,000 rows/page
4 threads
NOLOCK
Azure SQL
90s connect
5 retries
DTU-safe
Cautious
100 rows/batch
1 thread
Row verify
Ready to migrate
with confidence?
Cygenix handles the complexity — AI mapping, visual drag-and-drop, cross-engine migration (Postgres ↔ SQL Server), file imports (CSV, Excel, text), value translation, grouped execution plans, system parameters, flexible validation, project planning with Jira and Smartsheet sync, and performance tuning — so your team can focus on the migration, not the tooling.
Register interest → Read the docs