.svg){kind=small}
.svg){kind=small}
.svg){kind=small}
Complete the form below to get instant access to the Intelligence Checklist
By providing information in this form, you agree to Next Pathway’s Privacy Policy
Before a Migration or Modernization begins, you need to know exactly what's in your estate. This checklist walks the three phases that get you there — a full-estate scan, a unified Enterprise Intelligence Graph, and SLMs trained on it. Any source, any target.
Our SLMs scan the four layers of your legacy estate: column-level ETL logic parsed from source code, semantic meaning and lineage traced from actual data flow, real access and usage behavior, and the documents and SOPs around the code. Every table, job, report, and dependency cataloged — nothing gets missed downstream.
Everything scanned in Phase 1 resolves into a single governed graph. Logic, meaning, behavior, and knowledge merged into one contextual model, with cross-system relationships reconstructed from how data actually flows. Access rules built into the graph from day one, not bolted on later.
SLMs trained directly on your graph, validated against hundreds of real migrations rather than synthetic data. From here you can take either path — Migration, where SLMs transform, test, and deploy translated code to your target platform, or Modernization, where they map, define, and build certified data products. Both lead to AI readiness.
Lines of code translated automatically
Enterprise modernizations completed
Faster time-to-market for AI-ready infrastructure
A multinational insurance and financial services provider accelerated legacy application modernization with Databricks and Delta Lake.
Read the case study to see how Next Pathway delivered:
A leading insurance and financial services provider modernized legacy data workloads with Databricks automation.
.webp)
ENDERLE GROUP
.webp)
THE BLOOR GROUP
Global Financial Firm Modernizes with Snowflake Migration.
Thinking beyond migration?
We help you modernize your data platform, end to end.
.svg){kind=small}
.svg){kind=small}
.svg){kind=small}
