Migrate SSIS Pipelines to Azure Data Factory, Databricks, Spark, or Snowflake Using GenAI

Legacyleap replaces years of SSIS package analysis, refactoring, re-architecture, and validation with a GenAI modernization platform that migrates legacy SSIS pipelines while preserving data logic and downstream behavior.

Unleash Unmatched Modernization Velocity with Legacyleap

Legacyleap sets new benchmarks for application modernization initiatives using Gen AI

2-5 days

to assess and document the entire legacy application

~70 %

modernization automated by Gen AI

2x

Faster modernization timelines vs. vendors or in-house

100%

functional parity, validated and compliant

PLATFORM

An Agentic Platform Built for SSIS Modernization

SSIS pipelines hide behavior across packages, configurations, and execution paths. Legacyleap modernizes these pipelines by separating assessment, planning, execution, and validation into specialized agents, each aligned to a specific phase of the system.

Assessment Agent

Understand SSIS pipeline complexity before migration

Analyzes SSIS packages to surface execution dependencies, transformation risk, and configuration coupling that affect migration feasibility.

Technical debt analysis

Pipeline architecture drift

Security and configuration risks

Modernization hotspots

Migration effort and timeline estimate

Documentation agent

Export-ready documentation from your legacy SSIS packages

Generates accurate, export-ready documentation directly from SSIS packages and execution behavior.

Complete system inventory (SBOM)

Pipeline and transformation maps

Data contracts and integrations

PRDs, BRDs, FSDs

Dependency and integration maps

Recommendation agent

Define the right SSIS migration path

Evaluates pipeline structure and usage patterns to determine whether SSIS logic should move to Azure Data Factory, Databricks, Spark, or Snowflake.

Automated target stack recommendations

Step-by-step SSIS migration plan

Modernization agent

Migrate SSIS pipelines without disrupting production

Executes controlled migration by translating SSIS logic into cloud-native pipelines while preserving execution order and data behavior.

Converted pipeline definitions

Migration gap reports

Actionable to-do lists

Pull requests

Automated PR review

QA Agent

Validate data parity and pipeline behavior

Ensures modernized pipelines produce the same results as the original SSIS system before cutover.

Unit test cases

Regression test cases

Integration test cases

Data validation checks

Automated PR review

$0 Assessment

Test Legacyleap on Your SSIS Pipelines for $0

Run a real assessment on one SSIS system before committing to modernization.

You receive

Pipeline risk and complexity analysis
Modernization hotspots
Migration effort and timeline estimate
Execution-ready outputs

This can be used as a standalone SSIS assessment or as the starting point for a fully managed migration.

Migration Paths

SSIS Migration Paths Supported by Legacyleap

Different SSIS systems require different modernization outcomes. Legacyleap evaluates pipelines and executes the appropriate path end to end.

Legacy SSIS Application

SSIS to Azure Data Factory

For teams standardizing on Azure-native orchestration.

SSIS control flow, scheduling, and dependencies are mapped into ADF pipelines while preserving execution order and triggers.

SSIS to Databricks

For data platforms moving toward scalable transformation frameworks.

SSIS transformations are translated into Databricks workflows optimized for distributed processing and maintainability.

SSIS to Spark

For organizations adopting open, compute-driven data architectures.

Pipeline logic is converted into Spark-based execution models while retaining transformation semantics.

SSIS to Snowflake

For analytics-first modernization.

SSIS pipelines are restructured into Snowflake-native data workflows while preserving downstream reporting and data contracts.

Each migration path is determined by the platform, executed incrementally, and validated for functional parity before production rollout.

Is Legacyleap Right for Me?

Choose between full-service delivery or platform access, both built to get you to production faster and safer.

You bring the system. We bring the outcome.

Turnkey Modernization Services

We take full ownership from start to finish, combining engineering expertise with platform accountability.

Leverage your internal or SI teams with our platform.

Platform Licensing

Deploy Legacyleap within your environment and modernize at your own pace, with full control, tools, and support.

Technical Demo

Book a Legacyleap Technical Demo

This session is led by the CTO and walks through how SSIS pipelines are analyzed, migrated, and validated across real production systems.

You’ll see how control flow, transformations, and data parity are handled during migration.

How a legacy codebase is analyzed for structure, dependencies, and risk

How documentation, architecture maps, and system inventories are generated

How migration paths to C#, .NET, or React are determined

How code conversion is executed incrementally with pull requests

How functional parity is validated before production rollout

Frequently Asked Questions

Didn't find what you were looking for?

What is the safest way to migrate SSIS pipelines to modern platforms?

The safest approach is to separate assessment, migration, and validation instead of translating SSIS packages directly. Legacyleap does this by analyzing SSIS control flow, transformations, and dependencies first, then migrating pipelines incrementally and validating data parity before cutover.

What does a GenAI-powered SSIS migration platform actually do?

A GenAI-powered SSIS migration platform analyzes package structure, control flow, data flow tasks, and configuration logic automatically. Legacyleap uses this to generate migration plans, modernized pipelines, documentation, and validation artifacts instead of relying on manual discovery.

How do I know whether SSIS should move to ADF, Databricks, Spark, or Snowflake?

The target platform depends on how SSIS pipelines behave. Orchestration-heavy pipelines map well to Azure Data Factory, transformation-heavy pipelines fit Databricks or Spark, and analytics-first pipelines often move to Snowflake. Legacyleap evaluates pipeline structure and usage patterns to recommend the right path.

How long does an SSIS migration typically take?

Timelines depend on the number of packages, transformation complexity, and dependencies. With Legacyleap, assessment and planning typically take 2-5 days, while migration proceeds incrementally over weeks or months instead of years.

How is Legacyleap different from traditional SSIS migration services?

Traditional services rely on manual analysis and rewriting. Legacyleap uses an agentic platform to automate assessment, documentation, planning, migration, and validation, reducing timelines by upto 70%.