Software Modernization

Software modernization services that end with the old stack turned off.

We rebuild the legacy module, migrate its data and customers, and hand it over documented and tested — without pulling your core engineers off the roadmap.

  • AI implementation services
  • Your core team stays on the roadmap
  • Docs + automated tests at handover
  • Inside your SDLC and ISO 27001

Built with the leading AI platforms

NVIDIAAnthropic
Peter Enestrom, founder of Zaigo

Led by Peter Enestrom and the Zaigo AI & engineering team

YaleColumbia UniversityMicrosoft

The problem

Legacy application modernization starts with the module nobody understands anymore.

From two anonymized calls: a product-led SaaS CEO whose last legacy module keeps a $40K-a-month stack alive, and a data lead at a 95%-on-prem wealth manager. Different estates, same ask — rebuild what matters, migrate the data, turn the rest off.

  • One module holds the whole stack hostage

    A product you no longer want to support is the last thing running on a legacy stack costing $40K a month. It is an all-or-nothing light switch — the stack cannot go off until the module lives somewhere else.

  • Nobody understands the old system anymore

    The people who built it are gone, and the business rules live in the code. Every change is archaeology — and no AI agent can automate work on a system nobody can explain.

  • Your core engineers cannot be the ones who fix it

    Pulling your team off the new-platform roadmap to rebuild the old world costs you twice — once in the rebuild, once in the roadmap that slips while they do it.

  • The stack is a cost drag and a security drag

    In the buyer’s words: “both a big cost drag on the organization and mild security things holding us back.” Every compliance review keeps circling a stack you want gone.

  • Or the whole estate is on-prem and fragmented

    The wealth-tech version: 95% on-prem, two data warehouses, multiple CRMs, five versions of the same table — “aspirations to get out of 1999.” AI agents have nothing clean to stand on until the data is gold rather than bronze.

  • Rip-and-replace quotes miss the point

    You do not need to bulldoze everything and start again, and you do not need to boil the ocean. You need one module rebuilt, the data migrated, and the old stack turned off — then the AI work can start.

What staying put costs

The old stack bills you every month for standing still.

The meter runs every month the module stays where it is — and none of that spend moves the roadmap forward.

$40K/monthOne SaaS company’s legacy stack spend — kept alive by a single billing module the company no longer wants to support.
5 → 2Legacy tech stacks at that company after consolidation — the rebuild retires the last one.
95%Share of one wealth manager’s technology still on-prem — two data warehouses, multiple CRMs, shared drives that get swampy pretty quickly.

From anonymized calls — a product-led SaaS CEO (~1,000 buildings on the platform) and a wealth-tech data lead

How it works

Rebuild it, migrate the data, turn the old stack off.

A fixed-scope rebuild run by an outside team, inside your engineering standards. Legacy system migration without the big-bang rewrite of everything.

  1. 01

    Map what the legacy system actually does

    AI agents read the legacy codebase, the database, and the integrations alongside our engineers — every business rule, edge case, and report the old system quietly produces. The map becomes the rebuild spec, with nothing tribal left in it.

    AI reads the code, engineers verify
  2. 02

    Rebuild the functionality, migrate the data

    We rebuild the module on a clean, current stack — AI-accelerated, engineer-reviewed — and migrate the legacy data and customers across. The work lands in your repos, your CI/CD, your SDLC, so what ships is already yours.

    Your repos, your CI/CD
  3. 03

    Hand it over clean, then turn it off

    Full documentation and an automated test suite come with the handover — the safety net that means your team owns it from day one. Then the old stack goes off, and the monthly bill stops.

    Docs + tests, then decommission
Who you are hiring

Legacy software modernization without the next maintenance nightmare.

Application modernization services from a dev shop end in code and a departure. The buyer’s objection is our design brief: “I don’t want to hand off one maintenance nightmare for another.” Every engagement ends in a clean handover — documentation, automated tests, and a walkthrough — built to your SDLC and ISO 27001 controls, with role-based access and SSO where you require them.

And we build AI systems for a living. AI agents do the reading and the grunt work — extracting business rules from legacy code, drafting the test suites and docs — which is how the rebuild moves at AI speed without vibe-coding your production system. Once the stack is clean, those same agents are what plug in next: modernization is where automation starts.

Peter Enestrom, founder of Zaigo
Who builds it

Led by Peter Enestrom.

Co-Founder — leads AI & Engineering

Pete Enestrom

Every engagement is led personally by Pete, working with the Zaigo AI & engineering team from the two-week audit through the production handover. The person who scopes the work is the person who builds it.

Education
Yale & ColumbiaGraduate
Background
Microsoft & IntelFormer
Experience
Exited FounderVenture-Backed

Background

Questions

On-prem to cloud migration, data migration services, and other questions.

Straight answers, before you book anything.

What’s holding your business back?

A workflow ready for automation. An AI product you want to build. A problem that has sat on the roadmap for years. Let’s talk about what it would take to solve it.

Talk to Zaigo