modernlift.

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Enterprise modernization · Brownfield delivery

Legacy stack
to modern
on a deadline.

New slice live every 4–8 weeks. Full legacy retirement in 4–6 months. AI-assisted analysis paired with human expertise — no big-bang cutover.

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Brownfield delivery AI-led discovery Customer co-creation
One slice · 4–8 weeks to production
W1
Kickoff & analysis
AI scans codebase. Joint workshop pins scope, criteria, deltas.
W2
Docs & workflows
Architecture, domain, edge cases — captured as living specs.
W3–6
POC in production
Slice-by-slice rollout. Real users. Full test coverage.
W7–8
Hand-off & retro
Knowledge transfer to your team. Roadmap for next slice.
Full migration 4–6 months
The shape of the migration

One chance. One slice at a time.

Traditional path
M0M12M20CUTOVERALL OR NOTHINGDEVELOPMENT · NO VALUE SHIPPED
1 migration 1 rollback path 1 shot
ModernLift
M0M3M6 · DONEEACH SLICE REVERSIBLE
8 slices 8 rollback paths 1 controlled process
The challenge

Your business runs on systems built for yesterday.

Five forces hit at once. Most modernization programs solve one and inherit the other four.

01
Disconnected reality
Documentation drifted years ago. Tribal knowledge sits with the few who remember why.
02
Rising maintenance cost
A bigger share of every engineering hour goes to keeping the lights on, not building.
03
Aging tech & senior talent
The people who built the system are retiring. The graduates don’t want to maintain it.
04
Security & compliance risk
Unpatched runtimes. Audit findings. Vendor-supported clocks running out.
05
Poor UX & adoption
Internal users route around the system. Customer-facing flows feel a decade behind.
~70%
of modernization programs miss their stated business outcomes — over time, over budget, or quietly shelved. ModernLift exists to change that ratio.
What we see

Why 70% of modernization projects fail.

01
Big bang, parity last
Teams chase feature complete before validating parity. By the time gaps surface, sunk cost has won.
02
Business continuity disrupted
Cutover dates slip. Operations get caught in dual-running for quarters with no exit.
03
Innovation halts
Every team is paying down legacy debt. The product roadmap stops while the migration runs.
04
Subject-matter expertise lost
The system’s authors are not on the rebuild. Decisions get re-litigated and re-broken.
05
Years gap, value unrealized
Even on schedule, the business waits two-plus years for the first delta of value.
Dramatic divergence between plan and reality is the norm. We treat that as the starting point.
— Our operating premise
What modernization needs

Five things that have to be true at the same time.

01
Continuous operations during migration
The legacy system keeps running. Cutover risk is not concentrated on a date.
02
Validated parity at every step
Every slice is shadow-traffic checked against the legacy. Behavior, not just output.
03
Preserved institutional knowledge
Captured as living specs the team and the AI both read. Never re-discovered.
04
Modernization at low risk
Slice-by-slice rollout. Any slice can be rolled back without touching the next.
05
Incremental value delivery
New capability ships every 4–8 weeks. The roadmap doesn’t pause for the migration.
ModernLift is built to deliver all five — at once.
— The ModernLift promise
The approach

Three principles that change everything.

The non-negotiables beneath every engagement.

01
Preserve
Institutional memory
The system encodes decades of business reality. We capture it as living specs the AI and the team both read — before we touch a line.
  • + Codebase deep-read
  • + Domain capture workshops
  • + Living architecture docs
02
Transform
Slice-by-slice delivery
We split the monolith into slices and modernize one at a time. Each slice ships to production behind a feature flag. No cutover date.
  • + Slice-by-slice rollout (strangler pattern)
  • + Shadow-traffic validation
  • + 4–8 week production cadence
03
Validate
Parity-first safety
Every slice is checked against the legacy. Behavior parity, not just spec parity. The legacy is the source of truth until it is not.
  • + Shadow comparison
  • + Full test suite
  • + Roll-back at any boundary
How we deliver

A proprietary AI toolchain, in expert hands.

The same disciplined motion on every engagement — read the system, plan the work, ship validated slices — run by senior engineers, accelerated by our proprietary AI toolchain.

Discovery
AI-accelerated discovery
Our AI toolchain deep-reads your codebase, data, and docs and captures the behavior, edge cases, and domain rules nobody wrote down — as living specs your team owns.
  • — Behavior spec library
  • — Living architecture docs
  • — Edge-case catalog
  • — Open-format export
Planning
AI-assisted slice planning
It proposes the target architecture and a slice plan grounded in your actual code. Your senior engineers steer; the AI handles the volume.
  • — Slice planning
  • — Grounded in your code
  • — Parity shadowing
  • — Human-in-the-loop review
Delivery
Validated, audited shipping
Feature flags, shadow traffic, full CI/CD. Slices roll forward; any one can roll back without touching the next.
  • — Slice-by-slice rollout
  • — Shadow-traffic harness
  • — Full test suite
  • — Per-slice rollback
Knowledge without rollout is a report. Rollout without parity is a gamble. We deliver them as one motion.
— Why it's one motion, not a series of handoffs
How the migration plays out

Replace, slice by slice.

A facade in front of the legacy. Each slice routes one behavior to the modern stack — validated against the legacy in shadow — until nothing remains on the old runtime. The architecture community calls it the strangler-fig pattern; in practice it just means the new system grows around the old one until the old one is gone.

T+0m
Today
100% legacy
T+2m
Slice 1
5% migrated
T+4m
Slice 2
20% migrated
T+6m
Slice 3
55% migrated
T+8m
Cutover
100% modern
Legacy runtime Modern runtime · Every slice is rolled out behind a feature flag and shadow-validated.
Slice by slice
Each behavior migrates independently. No global cutover date.
Shadow first
Modern stack receives mirrored traffic. Discrepancies become tickets.
Promoted on parity
Live traffic flips once behavior matches. Roll-back is a flag.
Legacy retires last
When the last slice promotes, the old runtime is decommissioned.
The timeline

Two-to-three years of work — in four-to-six months.

AI-assisted analysis collapses discovery from months to weeks. Slice-by-slice delivery keeps the legacy revenue-safe while the modern stack earns its place. Based on engineering modeling — early engagements underway.

Traditional path
2–3 yrs
Multi-quarter discovery. Big-bang cutover. Innovation freezes. Value lands at the end — if it lands.
With ModernLift
~6× faster
4–6 mo
Continuous delivery in slices. Value lands every 4–8 weeks. Legacy stays warm until the last slice retires it.
Speed to first value
4–8 weeks
vs 6–9 months
Cutover risk
Per-slice
vs Big-bang
Innovation roadmap
Continues
vs Frozen
Knowledge retained
Captured as spec
vs Tribal & lost
Side by side

Same goal. Fundamentally different approach.

Dimension
ModernLift
Traditional SI / re-platform
Time to first production value
+ Incremental delivery every 4–8 weeks
— 6–9 months minimum
Risk model
+ Per-slice, behind feature flags
— Big-bang cutover; multi-quarter dual-running
Knowledge capture
+ Living specs co-owned by team + AI
— Tribal; lost when people leave
Roadmap during migration
+ Continues — new capability ships in slices
— Frozen for the duration
Parity validation
+ Shadow traffic, behavior-level
— Spec-level; gaps surface at cutover
Roll-back
+ Per-slice, feature-flag boundary
— Architectural; rarely exercised
How to start

Three entry points. Each de-risks the next.

Start small. Every engagement stops cleanly if the next one isn't right yet.

01
3–4 weeks
Discovery
Codebase + reality scan
AI-led deep-read of your codebase plus on-site workshops. You walk out with a documented baseline, a risk map, and a slicing plan.
You walk out with
  • + Living architecture doc
  • + Risk and dependency map
  • + Slicing plan with cost-of-delay
  • + Optional: pilot scope
02
6–10 weeks
Accelerator
First slice in production
We modernize one real slice — the highest-leverage one. End-to-end: design, build, shadow, promote. Your team works alongside ours throughout.
You walk out with
  • + One slice live in production
  • + Shadow-traffic harness
  • + Behavior parity report
  • + Rollback boundary established
03
4–18 months
Transformation
Replace the rest, slice by slice
Continuous slicing of the legacy until the runtime is retired. Your team takes increasing ownership as our role tapers — no hand-off cliff.
You walk out with
  • + Steady slice cadence
  • + Living spec library
  • + Team operating model
  • + Decommissioned legacy
You don't change to fit us

We meet your team where it is.

Your existing platforms, languages, and conventions are the constraint set we plan against.

01 Any stack
COBOL, RPG, PL/SQL, .NET, Java EE, mainframe DB2, AS/400.
02 Any modern target
TypeScript, Go, Python, Kotlin, Java 21 — your platform, your call.
03 Any cloud
AWS, Azure, GCP, on-prem, regulated air-gapped. Same playbook.
04 Any data shape
Batch, event-streamed, CDC. We meet the system’s grain.
05 Any CI/CD posture
Jenkins, GitHub Actions, GitLab, Azure DevOps. We slot in.
06 Any observability
OpenTelemetry, Splunk, Datadog, ELK. Shadow-traffic everywhere.
Let's start a conversation

Let's build your modern future.

30-minute discovery call. We'll walk your stack, your constraints, and where the highest-leverage first slice sits. No deck.

Let's talk → sales@modernlift.ai
3–4 wks
fixed-price discovery
4–8 wks
per production slice
10×
faster analysis
0
big-bang cutovers