Systems engineering, modeling, and simulation often involve complex toolchains, manual coding, and ensuring data integrity across various software tools and model components. This complexity can hinder efficient design iterations and collaboration, especially when integrating physics-based reasoning.

Artifact is an AI-native platform designed to streamline physics-based engineering workflows by integrating AI-driven physics reasoning with open-source engineering tools. The platform enables engineers to efficiently create simulations, design control systems, and optimize system-level designs. Artifact's semantic layer enforces physics principles, automates the assembly of analysis artifacts, and manages interfaces between software tools, data files, and model components. By maintaining a single-source-of-truth system specification, Artifact facilitates collaborative workflows and ensures data integrity across projects.

AI-driven physics reasoning engine that understands the physical world

Automated generation of 3D models in Engineering Sketchpad (ESP) format for packaging and configuration studies

Aerodynamics model generation using USAF Digital Datcom, parsed into Python code

Integration with the Python Control Systems Library for dynamics and controls problems

Collaborative workflows with a single-source-of-truth system specification

Specialized AI agents for tasks like system identification, software-in-the-loop testing, and Monte Carlo studies

Ability to run on-premise and integrate with proprietary, air-gapped company toolsets and data

Artifact is primarily targeted towards systems engineers, modeling and simulation specialists, and control systems designers working on physics-based engineering projects.