AI That Engineers and Transforms Entire LabVIEW Ecosystems

Meet GenVI. It maps your entire LabVIEW codebase into AI-aware knowledge, then connects it to Claude Code, GitHub Copilot, Codex, and Cursor, so you can understand, document, audit, and confidently change and modernize LabVIEW projects so it can interoperate with modern application stacks.

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For LabVIEW Teams Looking to Co-opt AI

You want an AI that reads your entire LabVIEW project, not just one VI at a time. You want an AI Agent to help perform SDLC for your LabVIEW projects. You want to modernize your LabVIEW framework to be multi-language-agnostic and interoperable with other modern tech stacks. You want a coding agent that understands your block diagrams and wiring the way it already understands text-based code.

GenVI does this. We built a system that reads VIs, libraries, classes, and projects, and turns them into an AI-aware model of your codebase. From there, any AI coding agent can answer real questions about your LabVIEW project: how it's built, where the risk is, and what it would take to change it.

What GenVI Can Do

Decode

Ask GenVI what a LabVIEW application does, why it's built that way, and where the risk sits, across every module and library in the codebase. It answers from the actual code behind it.

Design

Design new features and give accurate estimates on top of complex legacy code someone else built, backed by GenVI's understanding of your codebase and its dependencies. GenVI generates the design documentation your team actually needs, so no one has to reverse-engineer intent from code alone.

Audit

Validate code against your methodology, your coding standards, or another reference project, as development progresses. GenVI reads both the standard and the implementation and flags every deviation, even for a reviewer without LabVIEW expertise.

Debug

Catch issues in your LabVIEW code before a pull request ever merges, with GenVI reviewing every PR and GitHub issue directly on your repo. It's not a chatbot layer added on the side; it lives in the workflow your team already uses.

Modernize

GenVI surfaces reusable components, so your LabVIEW code can interoperate with modern application stacks and move towards a multi-language-agnostic framework with structural understanding, not just syntax conversion.

How It Works

A lightweight LabVIEW client parses your project, VIs, libraries, classes, and dependencies, which GenVI remembers in an AI-aware model. Every VI, every relationship, every wire traced and connected, enriched with AI-generated summaries of what each piece does.

An MCP server exposes this AI model to the AI coding agent your team already uses, including Claude Code, GitHub Copilot, Codex, and Cursor. Ask your agent about the architecture, the risk areas, or how to migrate a module, and it answers from your actual codebase, not a guess.

GenVI supports LabVIEW projects back to version 2013, so teams don't have to modernize their toolchain before they can start upgrading their code.

Built and Proven on Real LabVIEW Codebases

GenVI has processed LabVIEW instrument driver libraries spanning over 20,000 files, surfacing the edge cases (legacy file formats, malleable and express VIs) that only show up at real scale.

We're not a chatbot layer simply added onto LabVIEW. GenVI is Agentic. GenVI is a reviewer that lives in your workflow: connect it to your GitHub repos and it reviews issues and pull requests on LabVIEW code directly, the same way it does for any other codebase.

What GenVI Does Today, and What's Still Ahead

What Works Today

GenVI can work on code bases of 20,000+ LabVIEW files doing documentation, audit and modernization. GenVI is already Agentic, meaning it can run autonomously as a agent behind the scenes in doing code reviews, audit and design recommendations, support, etc. Importantly, GenVI runs within your IT environment with your approved models and infrastructure.

What's Still Ahead

We're working closely with a small number of LabVIEW teams to sharpen what GenVI supports and learn where it needs to get better. If you work on LabVIEW, get in touch with us. We're always looking to expand use cases of GenVI.

Choose How You Work With GenVI

Cloud

Start today. Connect your LabVIEW codebase, and use all five capabilities immediately. Your data stays isolated to your organization; no LabVIEW IP is shared across customers.

Secure On-Premise

Deploy GenVI entirely within your own infrastructure. Built for teams with strict data sovereignty requirements.

Outcomes Partner

Partner with Soliton to bring LabVIEW and AI into your workflows end to end. We own the delivery. You get the outcomes.

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FAQ

Frequently asked questions.

Everything you need to know about parsing, auditing, and modernizing LabVIEW codebases with GenVI.

What LabVIEW versions does GenVI support?+

GenVI works with LabVIEW projects back to version 2013, with some limitations on older or less common file types. We're actively broadening this coverage.

Which AI coding agents does GenVI work with? +

Claude Code, GitHub Copilot, Codex, and Cursor today, connected through GenVI's MCP server. If your team uses a different coding agent, talk to us; we're expanding this list.

Is my LabVIEW code and data secure? +

Your codebase stays isolated to your organization; no LabVIEW IP is shared across customers. If your team needs stricter data sovereignty, GenVI is also available as a Secure On-Premise deployment.

Can GenVI help if we need to move LabVIEW code to another language?+

Some teams do need to translate parts of a LabVIEW project into Python or C#. GenVI's architectural understanding supports that too, preserving design intent rather than converting syntax. Every codebase is different — talk to us about your specific situation.

Is GenVI ready for production use? +

GenVI is in active use today for understanding, auditing, and migrating LabVIEW codebases, and we're still early in expanding what it supports. We'd rather be upfront about that than overstate where things stand; talk to us about your specific codebase and we'll be honest about fit.

Does GenVI work with our existing GitHub workflow? +

Yes. Connected to your GitHub repo, GenVI reviews issues and pull requests on LabVIEW code directly, the same way it would for any other codebase.

Does GenVI work agentic?+

GenVI can run continuously in the background as an autonomous agent, picking up issues from your tracker, drafting fix strategies and design docs, and reviewing incoming pull requests without a human trigger. You can also invoke it directly when you want hands-on control.

Can GenVI handle very large LabVIEW codebases?+

Yes. GenVI has processed instrument driver libraries spanning 20,000+ files, including edge cases like legacy file formats and malleable/express VIs.

Does GenVI support redeveloping modules in web technologies (JS/TS), not just Python or C#?+

Some teams target Web alongside Python and .NET when redeveloping accelerator modules. Talk to us about your target stack. GenVI's architectural understanding isn't tied to one output language.

What kind of documentation does GenVI produce?+

GenVI generates design documentation and fix strategies grounded in your actual codebase, so that your team isn't reverse-engineering intent from code alone when planning changes or estimating new features.

Do we need to change our toolchain or coding agent to use GenVI?+

No. GenVI connects via MCP to the coding agent you already use — Claude Code, GitHub Copilot, Codex, or Cursor — so it fits into your existing workflow rather than replacing it.

What's the difference between the Cloud, Secure On-Premise, and Outcomes Partner options?+

Cloud gets you started fastest with all five capabilities and organization-isolated data. Secure On-Premise deploys GenVI entirely within your infrastructure for teams with data sovereignty requirements. Outcomes Partner has Soliton own delivery end-to-end. Talk to us about which fits your situation.

See what GenVI can do with your own LabVIEW codebase.

Cloud, on-premise, or fully managed. Your choice.

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