Legacy Migration
Legacy migrations often have critical business rules spread across pipelines, schemas, documentation, dependencies, and institutional knowledge. When that context is missed, the new system may run but fail to produce the intended business results.
Genesis agents use the enterprise context to recover business logic, then build the mappings, transformations, pipelines, tests, and documentation required for the modern platform. Prover verifies the migrated results and directs discrepancies back for correction before your team approves the outcome.
Migrate the System.
Preserve the Business.
Recover What the Business Depends On
Genesis examines schemas, pipelines, code, dependencies, documentation, and operational knowledge to reconstruct the requirements embedded in the legacy environment.
Complete the Migration Work
Genesis agents create the mappings, transformations, pipelines, tests, documentation, and implementation artifacts needed for the target platform.
Verify Outcomes, Not Just Code
Prover independently evaluates the migrated result, investigates material discrepancies, and directs corrections before the work is presented for approval.
Give Your Team Evidence and Control
Your team can review what was tested, what passed, what changed, and what still requires judgment before approving the outcome.
How Genesis Fits
Your Migration
Genesis is an agentic system that powers AI data workers to execute complete data workflows from start to finish—not AI assistants that just suggest code. Genesis agents research data sources, ingest data, map data from bronze source to gold targets , write code, create documentation, test data pipelines, commit git PRs, monitor pipelines and fix errors while learning from your environment.
Prover by Genesis is the independent evaluator that checks your AI-built migration against your business rules and gives coding agents the fixes needed to get it ready for your team’s approval. See how Prover works.
- Cursor – Suggests and writes code snippets (which is the easy part)→ you review → you execute
- Genesis – Researches context → inspects and understands data → maps data from the source → generate and runs data pipeline code → documents → creates and runs data pipeline tests → monitors—all ambiently. Think of it as hiring a junior data engineer vs. installing autocomplete.
Traditional Stack
- Fivetran for ingestion
- dbt for transformation
- Airflow for orchestration
- Monte Carlo for monitoring
Genesis Agents
- One autonomous agent platform that uses all of the tools in your existing stack
Genesis augments human data engineers, connects to and uses the traditional tools, and fits right into your existing data engineering / pipeline building / CI/CD process with agents that handle the entire workflow.
No. Genesis agents handle repetitive, undifferentiated work (source to target mapping, pipeline maintenance, monitoring, catalog updates) so your team can focus on strategic work (architecture, ML models, business analysis). Think "augmentation" not "replacement."
No. Genesis works with the stack already in place. It can use existing warehouses, orchestration tools, repositories, catalogs, communication systems, and CI/CD processes as part of an end-to-end workflow.
Genesis supports customer-controlled deployments across environments including Snowflake, Databricks, AWS, Azure, and containers. The exact configuration and security model depend on the customer’s architecture and requirements.
Contact us to schedule a demo. Our experts can show you how Genesis works, discuss the right starting point for your environment, and help your team get set up to try it.