Legacy System Modernization
Your most valuable data often sits in mainframes, on-prem databases and file shares. We connect it to modern AI safely and in stages, so you get value without a risky rewrite.
What's getting in the way
Legacy systems work, and that's why they're hard to replace. Rather than a multi-year rewrite, most organizations need a bridge: governed pipelines that expose the right data to AI while the core systems keep running.
Rewriting a core system to enable AI is expensive and risky. Instead, we build a governed bridge: change-data-capture from legacy databases, document extraction from archives and file shares, and APIs over systems that never had them. AI teams get current, permissioned data while the systems of record keep running.
- Data bridge: change-data-capture from legacy databases into a governed lakehouse
- Document AI: extraction from scanned forms, PDFs and file shares
- API layer: modern interfaces over systems that never had them
- Incremental retirement: replacing components only when there's a clear payoff
The path we follow
Discover
Catalogue legacy systems, data owners and the AI use cases that depend on them.
Bridge
CDC pipelines and document extraction into a governed lakehouse.
Expose
APIs and vector indexes with row-level permissions.
Retire
Replace legacy components only where the business case is clear.
How we deliver it
Cloud-to-AI Migration
Move legacy workloads and data platforms onto infrastructure that is ready for AI.
Explore service →SVC-04MLOps Pipeline Setup
Automate training, evaluation, deployment and monitoring so models ship like software.
Explore service →SVC-01Private & On-Prem LLM Deployment
Run open-weight models on your own servers or private cloud, with no data leaving your network.
Explore service →Common questions
Do you work with mainframes?
Yes, through standard CDC and file-based integration patterns, working with your mainframe team.
How do you handle scanned documents?
With OCR and layout-aware extraction models running inside your environment.
Find out what private AI would cost you.
A 45-minute call with an engineer, not a sales script. You'll leave with a rough architecture, a cost range and the next three steps.