Vnuli

AI tools for engineers of the physical world.

Vnuli lets engineers use the AI client they already work with to investigate engineering data through deterministic tools. The AI can ask Vnuli to inspect registered data, run calculations, and return bounded evidence with provenance.

Connect engineering data
-> use a qualified AI client
-> Vnuli performs deterministic engineering analysis
-> receive bounded, traceable evidence and provenance
-> continue investigating through follow-up questions

The AI is not the numerical authority. Vnuli performs the engineering computation and returns evidence the AI can use to explain results and guide the next question.

Install

Vnuli 0.1 is qualified on Windows 11 x86-64 with Python 3.12.

pip install vnuli

Verify the install:

vnuli --version
vnuli --help

First Use

From the project folder where you want Vnuli state to live:

vnuli setup
vnuli data add <source>
vnuli data list
vnuli data show <dataset>
vnuli mcp install <client>
vnuli mcp verify <client>

What those steps do:

• vnuli setup initializes Vnuli project state.
• vnuli data add <source> registers a supported engineering data source.
• vnuli data list shows registered datasets.
• vnuli data show <dataset> shows Vnuli's interpretation of a dataset.
• vnuli mcp install <client> configures a qualified AI client to launch Vnuli's local MCP server.
• vnuli mcp verify <client> verifies the local client configuration.

All qualified AI clients use the same local Vnuli server:

vnuli serve

Normal setup does not require hand-authored MCP JSON/TOML.

Supported Data

Vnuli supports documented engineering time-series layouts, not arbitrary files with matching extensions.

Current qualified data categories:

• CSV
• HDF5
• MATLAB MAT v5
• TDMS
• NASA Milling mill.mat reference data

See Vnuli Supported Data Layouts for the exact layouts, timebase behavior, metadata behavior, bounded-access notes, and unsupported-layout rules.

Supported AI Clients

Current AI-client compatibility status:

See Vnuli Supported AI Clients for tested versions/environments, configuration locations, limitations, and qualification details. Qualification of one tested version/environment does not certify every future client version, account type, operating system, or extension build.

Trust Model

Vnuli keeps engineering computation in deterministic tools:

• source data is registered and interpreted by Vnuli;
• engineering calculations are performed by Vnuli, not guessed by the AI;
• results include bounded evidence and provenance;
• the AI receives Vnuli tool results and explains or follows up from that evidence.

This separation is the core product boundary:

AI client
-> Vnuli engineering tools
-> deterministic computation
-> bounded evidence + provenance
-> AI explanation and follow-up

Learn More

• Supported Data Layouts
• Supported AI Clients