Get Started

From equation to production workflow — in one place

engicloud.ai gives you a library of +20,000 validated, Python-based engineering calculators spanning 20 disciplines and 110 subfields — each sourced from established engineering literature, implemented as tested Python functions, and ready to chain into executable modeling workflows on a visual canvas.

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What are “synthetic models”? Each calculator is a Python implementation of a known, published equation — auto-generated from curated literature, then validated against reference solutions with unit tests. They’re not AI guesses: they’re tested code for known physics.
1
Find & Create

Start with equations you can trust

Search over 20,000 calculators by physics concept, equation name, or engineering domain. Every calculator is a versioned Python function with typed inputs, outputs, units, and inline documentation — ready to run or customize.

encapsulate python code

safely wrap scripts into secure, deployable computational assets.

create a re-usable python-based model (calculator)

design modular mathematical logic for repeated engineering analysis.

combine different calculators into a modeling workflow (project)

visually link singular tools into automated analytical pipelines.

port your existing python code into re-usable calculators

transform legacy scripts into modular, ready-to-run analytical tools.

2
Build Workflows

Connect calculators into modeling pipelines

Drag calculators onto the visual canvas and wire outputs to inputs. Build multi-step workflows that chain thermodynamic tables, transport models, and custom equations into a single executable pipeline.

use expert-created python models (calculators)

leverage pre-built, vetted analytical frameworks designed by professionals.

choose from 80,000 synthetic models (calculators)

tap into a massive library of artificially generated functions.

solve coupled differential equations

concurrently analyze highly interconnected variables and multiphysics behaviors.

solve differential equations

seamlessly evaluate dynamic physical states and mathematical changes.

3
Enhance with AI

Let AI accelerate — not replace — your engineering

Use LLMs to generate new calculator code from natural-language descriptions, or apply ML methods for data-driven predictions. Every AI-generated model goes through the same validation pipeline as hand-written code.

use ML methods for predictions

apply advanced data-driven algorithms to forecast future engineering scenarios.

make live API calls to LLMs

quickly query cutting-edge language engines during runtime execution.

use an AI assistant to generate physics-based modelling workflows

direct intelligent agents to automatically map complete simulation pipelines.

use LLMs to generate new python-based models (calculators)

prompt artificial intelligence to instantly draft custom algorithmic logic.

4
Connect & Integrate

Bring in your data, tools, and knowledge

Connect to external databases, spreadsheets, and internal knowledge bases. Your workflows aren't isolated — they pull live data from the systems your team already uses.

interact with databases from different sources

seamlessly query and extract information across multiple external systems.

integrate and interact with spreadsheet / excel models

dynamically link and sync traditional tabular data and formulas.

integrate existing internal knowledge

centralize your proprietary company insights directly into the platform.

store material parameters into a database for re-use

securely archive physical properties for instant future retrieval.

5
Collaborate

Share models your team can actually use

Publish calculators and workflows so colleagues can run them on the visual canvas — even without writing Python. Version everything, control access, and build a shared engineering knowledge base.

create python modeling for someone else to use on the graphcial canvas

program backend logic for non-coders to easily arrange visually.

build projects for collaborations across teams

unite diverse organizational departments in joint computational efforts.

build your own private set of calculators and projects to share

curate secure, proprietary analytic toolkits to safely distribute internally.

How it all fits together

engicloud.ai has a simple object hierarchy. Understanding these four building blocks tells you everything about how the platform works.

𝑓

Equation

A mathematical relationship from published literature — e.g. Bernoulli's equation, Fourier's law, Navier-Stokes.

⚙

Calculator

A Python function implementing one equation — typed inputs/outputs, units, docs, unit tests. The atomic building block.

⬡

Workflow (Project)

A visual pipeline of connected calculators on the node canvas. Outputs of one feed inputs of the next.

👥

Team Library

A shared, access-controlled collection of calculators and workflows scoped to your organization.

Equation → Calculator → Workflow → Shared Library