The system no one fully remembers
The people who wrote it have moved on. The behavior is the spec. Vive reads the source as ground truth and reconstructs what it actually does.
Application modernization, supervised
Bring legacy systems
into daylight.
Vive sends a pipeline of specialized agents through your decades-old codebase — reading it, mapping it, and rebuilding it on a modern stack. An architect signs off at every gate. Nothing ships in the dark.
- Source
- COBOL · Java · Py2
- Target
- FastAPI · GCP · Postgres
- Gates
- 0
- Provenance
- every fact
A modernization isn't a rewrite you can hand to a black box. It's a multi-month act of judgment — and the judgment has to stay with your architects.
Not a generator. An instrument.
Agents propose; humans decide. Analysis, future-state, and spec each pause at a review gate. You hold the veto, in writing, in git.
Every claim carries its source
Each generated fact is tagged with where it came from and how confident the model is. No silent guesses dressed up as certainty.
The lifecycle
One pipeline, from archaeology to production.
Ten stages. Three places where everything stops and waits for a human.
agent stage
human review gate
live
Analysis
An AST pass decomposes the monolith into dependency-bound clusters, each explained in plain language.
Future state
A target architecture is proposed against your requirements, compliance posture, and cloud guardrails.
Generation swarm
Parallel agents write data, infrastructure, core logic, and frontend — then a validator checks them against spec.
Human-in-the-loop
The model proposes.
You decide.
At every gate the run halts. You read the artifact, ask the documentation agent questions in plain English, refine it, and only then approve. Approvals and rejections are commits — a permanent, auditable record of who decided what, and why.
- Review current-state docs before any planning begins
- Sign off on the future-state architecture
- Approve the implementation spec before a line is generated
future-state-architecture.md
Needs review
claude · proposes Cloud Run + Postgres over Cloud SQL 0.91
claude · maps 9 clusters → 6 services 0.88
you · "why not Cloud SQL for the ledger?"
claude · ledger needs row-level audit; Postgres + RLS keeps it in one engine
The swarm
A specialist for every layer.
Not one generalist guessing. A team of focused agents, each with one job.
Proof
AWS CardDemo, modernized.
A 1970s-era COBOL credit-card mainframe demo, rebuilt as a cloud-native Python service — to a working green screen.
Before
- LanguageCOBOL · CICS · JCL
- Runtimez/OS mainframe
- DataVSAM flat files
- UI3270 green screen
- Deploybatch, manual
After
- LanguagePython 3 · FastAPI
- RuntimeGCP Cloud Run
- DataPostgres + migrations
- UIReact, typed API
- DeployCI/CD, reproducible
0clusters mapped
0stories generated
0tests green
0human gates
Limited access
Modernize the system everyone's afraid to touch.
Vive is onboarding a small number of teams with large legacy estates. Tell us what you're carrying.
No demo theatre. We'll point Vive at a real subsystem of yours.