SOLUTIONS
Models and ideas to deployable, production-ready solutions
Through a combination of consulting expertise, SciML-powered development, and enterprise-grade support, we partner with teams to solve complex engineering and business problems with confidence.
SOLUTIONS
Models and ideas to deployable, production-ready solutions
Through a combination of consulting expertise, SciML-powered development, and enterprise-grade support, we partner with teams to solve complex engineering and business problems with confidence.
SOLUTIONS
Models and ideas to deployable, production-ready solutions
Through a combination of consulting expertise, SciML-powered development, and enterprise-grade support, we partner with teams to solve complex engineering and business problems with confidence.
SCIML
SciML-Powered Solutions
We build highly accurate, trustworthy Digital Twins and simulation-driven solutions that combine physics-based models with data-driven learning. These solutions are designed to be interpretable, robust, and ready for real-world use.
SCIML
SciML-Powered Solutions
We build highly accurate, trustworthy Digital Twins and simulation-driven solutions that combine physics-based models with data-driven learning. These solutions are designed to be interpretable, robust, and ready for real-world use.
Asset Health & Predictive Maintenance
Anticipate failures, reduce downtime, extend asset life
Asset Health & Predictive Maintenance
Anticipate failures, reduce downtime, extend asset life
Process Optimization
Improve efficiency, throughput, & operational performance
Process Optimization
Improve efficiency, throughput, & operational performance
Model-Based Control
Design and deploy controllers grounded in system dynamics
Model-Based Control
Design and deploy controllers grounded in system dynamics
Design Optimization
Explore design spaces faster and with greater confidence
Design Optimization
Explore design spaces faster and with greater confidence
Internal or External Simulation Tools
Custom tools such as performance predictors for sales teams or decision-support dashboards
Internal or External Simulation Tools
Custom tools such as performance predictors for sales teams or decision-support dashboards
Powered by Julia: the Standard for technical and scientific computing
Vibrant Open-Source Ecosystem
Julia’s expansive and continuously growing ecosystem fosters collaboration and accelerates code deployment. Its readability and maintainability ensure long-term sustainability of projects.
High Performance
Julia’s just-in-time (JIT) compilation system delivers lightning-fast execution, with performance gains of 100-1000x over legacy languages making it an ideal choice for HPC applications in computing solutions.
Ease of Use
Julia’s intuitive syntax is easy to learn for developers familiar with Python or MATLAB, enabling rapid skill acquisition and minimizing training time.
Advanced Parallelism
Built-in support for parallel computing allows for efficient execution of concurrent tasks, maximizing resource utilization and reducing project timelines.
Math-Friendly Syntax
Julia’s syntax is tailored for complex mathematical operations, streamlining the development process for scientific and engineering applications.
Automatic Differentiation
Simplify the creation of algorithms and models that require gradients and derivatives, reducing coding complexity and enhancing model accuracy.
Native GPU Support
Harness the full potential of GPUs to accelerate computational tasks and simulations, driving innovation in data-intensive projects.
Vibrant Open-Source Ecosystem
Julia’s expansive and continuously growing ecosystem fosters collaboration and accelerates code deployment. Its readability and maintainability ensure long-term sustainability of projects.
High Performance
Julia’s just-in-time (JIT) compilation system delivers lightning-fast execution, with performance gains of 100-1000x over legacy languages making it an ideal choice for HPC applications in computing solutions.
Ease of Use
Julia’s intuitive syntax is easy to learn for developers familiar with Python or MATLAB, enabling rapid skill acquisition and minimizing training time.
Advanced Parallelism
Built-in support for parallel computing allows for efficient execution of concurrent tasks, maximizing resource utilization and reducing project timelines.
Math-Friendly Syntax
Julia’s syntax is tailored for complex mathematical operations, streamlining the development process for scientific and engineering applications.
Automatic Differentiation
Simplify the creation of algorithms and models that require gradients and derivatives, reducing coding complexity and enhancing model accuracy.
Native GPU Support
Harness the full potential of GPUs to accelerate computational tasks and simulations, driving innovation in data-intensive projects.
Vibrant Open-Source Ecosystem
Julia’s expansive and continuously growing ecosystem fosters collaboration and accelerates code deployment. Its readability and maintainability ensure long-term sustainability of projects.
High Performance
Julia’s just-in-time (JIT) compilation system delivers lightning-fast execution, with performance gains of 100-1000x over legacy languages making it an ideal choice for HPC applications in computing solutions.
Ease of Use
Julia’s intuitive syntax is easy to learn for developers familiar with Python or MATLAB, enabling rapid skill acquisition and minimizing training time.
Advanced Parallelism
Built-in support for parallel computing allows for efficient execution of concurrent tasks, maximizing resource utilization and reducing project timelines.
Math-Friendly Syntax
Julia’s syntax is tailored for complex mathematical operations, streamlining the development process for scientific and engineering applications.
Automatic Differentiation
Simplify the creation of algorithms and models that require gradients and derivatives, reducing coding complexity and enhancing model accuracy.
Native GPU Support
Harness the full potential of GPUs to accelerate computational tasks and simulations, driving innovation in data-intensive projects.
Vibrant Open-Source Ecosystem
Julia’s expansive and continuously growing ecosystem fosters collaboration and accelerates code deployment. Its readability and maintainability ensure long-term sustainability of projects.
High Performance
Julia’s just-in-time (JIT) compilation system delivers lightning-fast execution, with performance gains of 100-1000x over legacy languages making it an ideal choice for HPC applications in computing solutions.
Ease of Use
Julia’s intuitive syntax is easy to learn for developers familiar with Python or MATLAB, enabling rapid skill acquisition and minimizing training time.
Advanced Parallelism
Built-in support for parallel computing allows for efficient execution of concurrent tasks, maximizing resource utilization and reducing project timelines.
Math-Friendly Syntax
Julia’s syntax is tailored for complex mathematical operations, streamlining the development process for scientific and engineering applications.
Automatic Differentiation
Simplify the creation of algorithms and models that require gradients and derivatives, reducing coding complexity and enhancing model accuracy.
Native GPU Support
Harness the full potential of GPUs to accelerate computational tasks and simulations, driving innovation in data-intensive projects.
Powered by Julia: the Standard for technical and scientific computing
Vibrant Open-Source Ecosystem
Julia’s expansive and continuously growing ecosystem fosters collaboration and accelerates code deployment. Its readability and maintainability ensure long-term sustainability of projects.
High Performance
Julia’s just-in-time (JIT) compilation system delivers lightning-fast execution, with performance gains of 100-1000x over legacy languages making it an ideal choice for HPC applications in computing solutions.
Ease of Use
Julia’s intuitive syntax is easy to learn for developers familiar with Python or MATLAB, enabling rapid skill acquisition and minimizing training time.
Advanced Parallelism
Built-in support for parallel computing allows for efficient execution of concurrent tasks, maximizing resource utilization and reducing project timelines.
Math-Friendly Syntax
Julia’s syntax is tailored for complex mathematical operations, streamlining the development process for scientific and engineering applications.
Automatic Differentiation
Simplify the creation of algorithms and models that require gradients and derivatives, reducing coding complexity and enhancing model accuracy.
Native GPU Support
Harness the full potential of GPUs to accelerate computational tasks and simulations, driving innovation in data-intensive projects.
Vibrant Open-Source Ecosystem
Julia’s expansive and continuously growing ecosystem fosters collaboration and accelerates code deployment. Its readability and maintainability ensure long-term sustainability of projects.
High Performance
Julia’s just-in-time (JIT) compilation system delivers lightning-fast execution, with performance gains of 100-1000x over legacy languages making it an ideal choice for HPC applications in computing solutions.
Ease of Use
Julia’s intuitive syntax is easy to learn for developers familiar with Python or MATLAB, enabling rapid skill acquisition and minimizing training time.
Advanced Parallelism
Built-in support for parallel computing allows for efficient execution of concurrent tasks, maximizing resource utilization and reducing project timelines.
Math-Friendly Syntax
Julia’s syntax is tailored for complex mathematical operations, streamlining the development process for scientific and engineering applications.
Automatic Differentiation
Simplify the creation of algorithms and models that require gradients and derivatives, reducing coding complexity and enhancing model accuracy.
Native GPU Support
Harness the full potential of GPUs to accelerate computational tasks and simulations, driving innovation in data-intensive projects.
Vibrant Open-Source Ecosystem
Julia’s expansive and continuously growing ecosystem fosters collaboration and accelerates code deployment. Its readability and maintainability ensure long-term sustainability of projects.
High Performance
Julia’s just-in-time (JIT) compilation system delivers lightning-fast execution, with performance gains of 100-1000x over legacy languages making it an ideal choice for HPC applications in computing solutions.
Ease of Use
Julia’s intuitive syntax is easy to learn for developers familiar with Python or MATLAB, enabling rapid skill acquisition and minimizing training time.
Advanced Parallelism
Built-in support for parallel computing allows for efficient execution of concurrent tasks, maximizing resource utilization and reducing project timelines.
Math-Friendly Syntax
Julia’s syntax is tailored for complex mathematical operations, streamlining the development process for scientific and engineering applications.
Automatic Differentiation
Simplify the creation of algorithms and models that require gradients and derivatives, reducing coding complexity and enhancing model accuracy.
Native GPU Support
Harness the full potential of GPUs to accelerate computational tasks and simulations, driving innovation in data-intensive projects.
Vibrant Open-Source Ecosystem
Julia’s expansive and continuously growing ecosystem fosters collaboration and accelerates code deployment. Its readability and maintainability ensure long-term sustainability of projects.
High Performance
Julia’s just-in-time (JIT) compilation system delivers lightning-fast execution, with performance gains of 100-1000x over legacy languages making it an ideal choice for HPC applications in computing solutions.
Ease of Use
Julia’s intuitive syntax is easy to learn for developers familiar with Python or MATLAB, enabling rapid skill acquisition and minimizing training time.
Advanced Parallelism
Built-in support for parallel computing allows for efficient execution of concurrent tasks, maximizing resource utilization and reducing project timelines.
Math-Friendly Syntax
Julia’s syntax is tailored for complex mathematical operations, streamlining the development process for scientific and engineering applications.
Automatic Differentiation
Simplify the creation of algorithms and models that require gradients and derivatives, reducing coding complexity and enhancing model accuracy.
Native GPU Support
Harness the full potential of GPUs to accelerate computational tasks and simulations, driving innovation in data-intensive projects.
Powered by Julia: the Standard for technical and scientific computing
Vibrant Open-Source Ecosystem
Julia’s expansive and continuously growing ecosystem fosters collaboration and accelerates code deployment. Its readability and maintainability ensure long-term sustainability of projects.
High Performance
Julia’s just-in-time (JIT) compilation system delivers lightning-fast execution, with performance gains of 100-1000x over legacy languages making it an ideal choice for HPC applications in computing solutions.
Ease of Use
Julia’s intuitive syntax is easy to learn for developers familiar with Python or MATLAB, enabling rapid skill acquisition and minimizing training time.
Advanced Parallelism
Built-in support for parallel computing allows for efficient execution of concurrent tasks, maximizing resource utilization and reducing project timelines.
Math-Friendly Syntax
Julia’s syntax is tailored for complex mathematical operations, streamlining the development process for scientific and engineering applications.
Automatic Differentiation
Simplify the creation of algorithms and models that require gradients and derivatives, reducing coding complexity and enhancing model accuracy.
Native GPU Support
Harness the full potential of GPUs to accelerate computational tasks and simulations, driving innovation in data-intensive projects.
Vibrant Open-Source Ecosystem
Julia’s expansive and continuously growing ecosystem fosters collaboration and accelerates code deployment. Its readability and maintainability ensure long-term sustainability of projects.
High Performance
Julia’s just-in-time (JIT) compilation system delivers lightning-fast execution, with performance gains of 100-1000x over legacy languages making it an ideal choice for HPC applications in computing solutions.
Ease of Use
Julia’s intuitive syntax is easy to learn for developers familiar with Python or MATLAB, enabling rapid skill acquisition and minimizing training time.
Advanced Parallelism
Built-in support for parallel computing allows for efficient execution of concurrent tasks, maximizing resource utilization and reducing project timelines.
Math-Friendly Syntax
Julia’s syntax is tailored for complex mathematical operations, streamlining the development process for scientific and engineering applications.
Automatic Differentiation
Simplify the creation of algorithms and models that require gradients and derivatives, reducing coding complexity and enhancing model accuracy.
Native GPU Support
Harness the full potential of GPUs to accelerate computational tasks and simulations, driving innovation in data-intensive projects.
Vibrant Open-Source Ecosystem
Julia’s expansive and continuously growing ecosystem fosters collaboration and accelerates code deployment. Its readability and maintainability ensure long-term sustainability of projects.
High Performance
Julia’s just-in-time (JIT) compilation system delivers lightning-fast execution, with performance gains of 100-1000x over legacy languages making it an ideal choice for HPC applications in computing solutions.
Ease of Use
Julia’s intuitive syntax is easy to learn for developers familiar with Python or MATLAB, enabling rapid skill acquisition and minimizing training time.
Advanced Parallelism
Built-in support for parallel computing allows for efficient execution of concurrent tasks, maximizing resource utilization and reducing project timelines.
Math-Friendly Syntax
Julia’s syntax is tailored for complex mathematical operations, streamlining the development process for scientific and engineering applications.
Automatic Differentiation
Simplify the creation of algorithms and models that require gradients and derivatives, reducing coding complexity and enhancing model accuracy.
Native GPU Support
Harness the full potential of GPUs to accelerate computational tasks and simulations, driving innovation in data-intensive projects.
Vibrant Open-Source Ecosystem
Julia’s expansive and continuously growing ecosystem fosters collaboration and accelerates code deployment. Its readability and maintainability ensure long-term sustainability of projects.
High Performance
Julia’s just-in-time (JIT) compilation system delivers lightning-fast execution, with performance gains of 100-1000x over legacy languages making it an ideal choice for HPC applications in computing solutions.
Ease of Use
Julia’s intuitive syntax is easy to learn for developers familiar with Python or MATLAB, enabling rapid skill acquisition and minimizing training time.
Advanced Parallelism
Built-in support for parallel computing allows for efficient execution of concurrent tasks, maximizing resource utilization and reducing project timelines.
Math-Friendly Syntax
Julia’s syntax is tailored for complex mathematical operations, streamlining the development process for scientific and engineering applications.
Automatic Differentiation
Simplify the creation of algorithms and models that require gradients and derivatives, reducing coding complexity and enhancing model accuracy.
Native GPU Support
Harness the full potential of GPUs to accelerate computational tasks and simulations, driving innovation in data-intensive projects.
Dyad
Dyad Support and Consulting
Expert support and consulting to help organizations adopt and scale Dyad from initial onboarding to advanced, customized applications.
Dyad
Dyad Support and Consulting
Expert support and consulting to help organizations adopt and scale Dyad from initial onboarding to advanced, customized applications.
How we help
Getting started with Dyad
Advanced Dyad workflows and applications
Development of custom Dyad-based solutions tailored to your domain
Past Engagements
Legacy code conversion
Julia code optimization for performance and scalability
JuliaC support
Model library creation and standardization
Model debugging and validation
JuliaSure
Enterprise Support for Mission-Critical Systems
For organizations running Julia in production, JuliaSure provides enterprise-grade support and maintenance to reduce risk and ensure long-term success.
JuliaSure
Enterprise Support for Mission-Critical Systems
For organizations running Julia in production, JuliaSure provides enterprise-grade support and maintenance to reduce risk and ensure long-term success.
Development & Production Support
End-to-end assistance for building, deploying, and maintaining Julia applications in production environments.
Expert Guidance from Core Contributors
Direct support from the creators and core developers of the Julia language, offering deep expertise across the ecosystem.
Open-Source Ecosystem Support
Help with managing and troubleshooting open-source Julia packages to ensure compatibility and stability across projects.
Proactive Monitoring & Advanced Debugging
Continuous monitoring and powerful debugging capabilities to detect, diagnose, and resolve issues before they affect systems.
Priority Issue Resolution
Accelerated response and resolution for technical issues that impact production systems.
Upgrade Visibility & Risk Protection
Early insights into upcoming changes and indemnification to reduce operational and legal risks in production environments.
Development & Production Support
End-to-end assistance for building, deploying, and maintaining Julia applications in production environments.
Expert Guidance from Core Contributors
Direct support from the creators and core developers of the Julia language, offering deep expertise across the ecosystem.
Open-Source Ecosystem Support
Help with managing and troubleshooting open-source Julia packages to ensure compatibility and stability across projects.
Proactive Monitoring & Advanced Debugging
Continuous monitoring and powerful debugging capabilities to detect, diagnose, and resolve issues before they affect systems.
Priority Issue Resolution
Accelerated response and resolution for technical issues that impact production systems.
Upgrade Visibility & Risk Protection
Early insights into upcoming changes and indemnification to reduce operational and legal risks in production environments.
From Strategy to Production
Whether you are modernizing legacy models, building digital twins, optimizing operations, or deploying AI-driven engineering workflows, JuliaHub offers the expertise, tooling, and support to help you succeed.
From Strategy to Production
Whether you are modernizing legacy models, building digital twins, optimizing operations, or deploying AI-driven engineering workflows, JuliaHub offers the expertise, tooling, and support to help you succeed.
Scientifically grounded and trustworthy
Scientifically grounded and trustworthy
Scalable from prototype to production
Scalable from prototype to production
Maintainable over the full lifecycle of your systems
Maintainable over the full lifecycle of your systems
Talk to Our Experts
Have a complex problem or a specific use case in mind? JuliaHub Consulting can help you define, build, and deploy the right solution, faster.
We’ll use your information to respond to your inquiry and, if applicable, classify your interest for relevant follow-up regarding our products. If you'd like to receive our newsletter and product updates, please check the box above. You can unsubscribe at any time. Learn more in our Privacy Policy.
Get a Demo
Discover how Dyad, JuliaHub, and Pumas can improve your modeling and simulation workflows.
Enterprise Support
Leverage our developers, engineers and data scientists to help you build new solutions.
Custom Solutions
Have a complex setup that needs a custom solution? We are here to help.
Talk to Our Experts
Have a complex problem or a specific use case in mind? JuliaHub Consulting can help you define, build, and deploy the right solution, faster.
We’ll use your information to respond to your inquiry and, if applicable, classify your interest for relevant follow-up regarding our products. If you'd like to receive our newsletter and product updates, please check the box above. You can unsubscribe at any time. Learn more in our Privacy Policy.
Talk to Our Experts
Have a complex problem or a specific use case in mind? JuliaHub Consulting can help you define, build, and deploy the right solution, faster.
We’ll use your information to respond to your inquiry and, if applicable, classify your interest for relevant follow-up regarding our products. If you'd like to receive our newsletter and product updates, please check the box above. You can unsubscribe at any time. Learn more in our Privacy Policy.
Get a Demo
Discover how Dyad, JuliaHub, and Pumas can improve your modeling and simulation workflows.
Enterprise Support
Leverage our developers, engineers and data scientists to help you build new solutions.
Custom Solutions
Have a complex setup that needs a custom solution? We are here to help.