Custom AI agent · Documents & Data
AI Data Migration Mapping Agent
Move data with a map your team can review.
Translate legacy fields into a reviewable target schema with documented transformations, lineage, and exception handling.
- Less ambiguity between legacy and target fields
- Visible transformations before migration runs
- Traceable exceptions and unmapped data
Starting at $300 USD/month
Starting price is $300 USD/month for a tailored solution. Your final proposal defines the scope, deliverables and payment terms. Data connections, record volume, transformation complexity, testing, hosting, monitoring and ongoing support are scoped and priced before work begins.
What is an AI data migration mapping agent?
An AI data migration mapping agent helps teams translate records from a legacy system into a new schema without relying on undocumented assumptions. It compares source and destination fields, proposes mappings and transformations, flags incompatible values, and keeps the reasoning and lineage behind each decision. Tranki designs the workflow around your data model, migration waves, validation rules, and owners. It can accelerate mapping work, but it does not approve a migration or change production data without a controlled process.
What it can map
Compare source and target schemas
Inventory fields, types, keys, relationships, enumerations, required values, and constraints so gaps are visible before a migration plan is approved.
Propose field mappings
Relate legacy fields to target fields using names, descriptions, sample values, business context, and approved mapping patterns, while separating strong proposals from uncertain ones.
Describe transformations
Document format conversions, code translations, concatenation, splitting, defaults, lookups, and conditional logic needed to make a source value valid for the destination.
Track lineage and exceptions
Preserve source-to-target references, unmapped fields, rejected values, ownership, validation outcomes, and decisions across migration waves.
Where it can help
Replacing a core business system
Build a reviewable map from a legacy CRM, ERP, case platform, or database into a modern replacement before the first migration wave is scheduled.
Consolidating regional datasets
Align country or team-specific schemas, codes, date formats, and required fields into a shared target model while preserving local exceptions for review.
Moving a product or data platform
Translate event attributes, customer records, catalog fields, or operational history into a new warehouse, application, or analytics model with explicit validation rules.
How it works
A step-by-step workflow your team can review before launch.
Set the migration boundary
Tranki captures the source systems, target schema, record types, migration waves, owners, security rules, and the definition of an accepted mapping.
Inspect schemas and samples
The workflow compares permitted metadata and representative values, identifies type and relationship differences, and marks fields that need clarification.
Draft mappings and transformations
The agent proposes source-to-target links, conversion logic, code lookups, defaults, and exception paths with evidence from the approved inputs.
Review, validate, and version
Data owners approve or revise the map, test representative records, record unresolved issues, and version the mapping before a controlled migration run.
Built around your business
What we configure
- Source and target schemas, field ownership, key strategy, relationship rules, and migration-wave scope
- Transformation logic, code tables, defaults, null handling, date and locale formats, and validation thresholds
- Review queues, technical and business approvers, lineage requirements, exception routing, and change history
- Approved database, API, CRM, ERP, warehouse, data-lake, spreadsheet, or documentation connections
What we need from you
- Source and target schema documentation or approved metadata access, plus representative sample records
- A migration owner and domain reviewers who can confirm business meaning, codes, keys, and required fields
- A defined validation, rollback, access, retention, and sensitive-data handling process
- A destination test environment or other safe place to validate mappings before production use
Clear boundaries before launch
What it will not do
The agent does not execute a migration, decide undocumented business meaning, invent missing source values, or approve a target schema. A similar field name is not proof of equivalence. Destructive transformations, identity resolution, financial or regulated records, missing code definitions, and ambiguous relationships require qualified human review and a tested rollback or reconciliation plan.
How success is measured
Track mapping coverage, percentage of fields approved, unmapped and ambiguous fields, transformation-test pass rate, source-to-target reconciliation, rejected records, defect discovery before cutover, review effort, and rollback or rework. A successful mapping reduces migration risk without hiding unresolved decisions.
Frequently asked questions
What does an AI data migration mapping agent do?
It compares source and target schemas, proposes field mappings and transformations, identifies gaps, and keeps a reviewable record of decisions and exceptions. It supports planning and validation rather than silently moving data.
Can it run the migration for us?
The starting workflow is for mapping, review, and validation. A controlled execution step can be scoped separately with permissions, testing, reconciliation, and rollback requirements.
How does it handle fields with different meanings?
It uses available schema descriptions, sample values, business context, and reviewer feedback to propose a relationship. Ambiguous or unsupported meaning stays flagged until an owner confirms it.
Can it document transformations and code changes?
Yes. The mapping can record conversions, splits, joins, defaults, lookups, enum translations, date formats, null behavior, and validation rules that your team approves.
What if a source field has no destination?
The workflow records it as unmapped, captures a reason or proposed disposition, and routes it to the appropriate owner. It should not discard information or invent a target field.
Can it map multiple migration waves?
Yes. We can organize mappings by record type, source, target, release, owner, dependency, and version so changes are reviewed before each approved wave.
What is included in the $300/month starting price?
The starting price covers a scoped custom solution baseline. Your proposal defines the schemas, data sources, mapping volume, transformations, testing, integrations, hosting, monitoring, and support included.
