Q

2.0

๐Ÿ”€ Migration & Integration

From 18 months and a dozen consultants to 6 weeks and one analyst.

Most data migrations are a year of mapping spreadsheets, a quarter of broken pipelines, and a Friday of finger-pointing. xAQUA reads source systems in place, learns their structure, maps them to your target schema, and ships โ€” without custom ETL code or armies of consultants.

Use Case ยท 03
๐Ÿ”€
The Migration Trap

Most migrations fail. The successful ones cost more than the platform.

Gartner says 50% of data migrations exceed budget, timeline, or scope. The reason is always the same: it's all custom code, all the way down.

๐Ÿ“†
18+ month timelines
Discovery alone takes a quarter. Mapping takes two more. Then the engineering team builds custom ETL, the test team writes custom validation, and the executive team writes a custom apology.
18+ mo
typical enterprise migration timeline
๐Ÿ’ฐ
Consultant-heavy billing
Big four firms staff 12 analysts at $300/hr for nine months. Half the budget goes to mapping spreadsheets that get thrown out when scope changes.
2-5ร—
typical budget overrun
๐Ÿงฑ
Vendor-locked target
You migrated off the legacy. Now you're locked into the new vendor's bespoke API, their proprietary schema, their pricing model. You traded one cage for another.
1-of-N
systems that ever get fully retired
How xAQUA Fixes It

Read in place. Map semantically. Ship in weeks.

xAQUA federates across source systems without moving data, learns their semantic structure via SemantIQ, and lets you describe the target schema in business terms. The migration becomes a configuration, not a custom-code project.

01

Federate first, decide later

Connect to Snowflake, Databricks, Postgres, Salesforce, files in S3 โ€” whatever you've got. xAQUA reads metadata, samples, and lineage without copying data. You can query across all of it on day one.

SemantIQFederationZero-ETL
02

AI-assisted semantic mapping

The Data Steward agent proposes mappings between source and target โ€” column-by-column, with similarity scores, sample comparisons, and lineage. Analysts review and approve; they don't write the mapping by hand.

AI Data StewardAuto-MappingBusiness Glossary
03

Composer builds the pipeline

Once mappings are approved, Composer generates the transformation pipeline โ€” declarative, version-controlled, testable. No bespoke ETL code. No proprietary DAG language.

ComposerDeclarative Pipelinesdbt-compatible
04

Validate continuously

Qualix runs reconciliation between source and target every hour. Row counts, distributions, business-rule checks. When something drifts, you find out before the auditor does.

QualixReconciliationDrift Detection
The Migration Flow

Federate. Map. Compose. Validate. Ship.

xAQUA reads source systems in place, lets your team map semantically rather than column-by-column, and ships transformations as governed, version-controlled pipelines โ€” with continuous reconciliation against the source.

FROM xAQUA · ONE ANALYST, NO CUSTOM CODE TO Legacy Mainframe DB2 ยท COBOL copybooks On-prem Oracle benefits ยท eligibility Salesforce / SaaS CRM ยท APIs ยท files 01 Federate read in place SemantIQ scans metadata ยท samples no data copied 02 Map semantically AI Steward proposes column-by-column analyst approves 03 Compose no custom ETL Composer generates declarative pipeline version controlled 04 Validate Qualix reconciles continuous Snowflake target cloud DW Databricks target lakehouse MotherDuck target duckdb cloud โ†บ Continuous source-to-target reconciliation โฌ† 18 months & 12 consultants โ†’ 6 weeks & 1 analyst. Zero custom ETL code. Federation reads in place. AI proposes mappings. Composer generates declarative pipelines. Qualix reconciles continuously.
Source systemsxAQUA mapping & orchestrationTarget schema / platformContinuous reconciliation
🤝
xAQUA augments your migration team, not replaces it. Architects stop hand-writing mapping spreadsheets โ€” and start reviewing AI-proposed mappings, governing the target schema, and shipping in weeks.
18mo โ†’ 6wk
Migration Speed
Time from kickoff to first production cutover
1 Analyst
Team Size
vs. 12-person consultant engagement
Zero
Custom Code
Declarative mappings, no bespoke ETL
100%
Reconciled
Continuous source-to-target validation
Customer Story ยท In Production
A regulated Salesforce data migration shipped in 6 weeks, one analyst, zero custom code.
The original plan was an 18-month engagement with a global SI, $4M of services, and a 40-page mapping spreadsheet. xAQUA federated the source, auto-proposed mappings via SemantIQ, generated the pipeline through Composer, and reconciled continuously with Qualix. One analyst owned the project. The cutover happened in six weeks, with zero custom code and complete lineage on every record.
18mo โ†’ 6wk
Total project duration
12 โ†’ 1
Team size at cutover
0 lines
Custom ETL code written
Ready to start?

Stop running a year-long migration project.
Ship in weeks.

See how xAQUA federates your sources, AI-maps to your target, and ships migrations without custom code โ€” in a 30-minute demo on your stack.