Open-Source Scientific Computing
High-performance computing in Julia, Python, and R. We rapidly tailor open-source and dual-use technologies to unique mission requirements — from concept to deployment.
We build fast, high-fidelity models, digital twins, and scientific AI for our clients' hardest problems — uniting domain expertise, open-source scientific computing, and disciplined execution.
Trusted across the defense, research & innovation community
We align diverse stakeholders by speaking the four core dialects of successful industry–government collaboration. Innovation only matters when it can be applied to deliver real mission outcomes — so we lead multidisciplinary teams that span government, universities, and small businesses.
It starts with a clear purpose that defines success. Innovation matters only when it delivers real mission outcomes.
Great technology doesn't matter if you can't navigate acquisition and get solutions deployed quickly.
We bring deep domain and technical expertise to identify when emerging technology can dramatically improve outcomes.
Lasting innovation depends on viability — we develop dual-use solutions with long-term value for customers, partners and investors.
We integrate domain expertise, technical innovation, business acumen, and pragmatic execution to turn ideas into transformational capabilities.
High-performance computing in Julia, Python, and R. We rapidly tailor open-source and dual-use technologies to unique mission requirements — from concept to deployment.
Julia's SciML ecosystem to build high-fidelity models of complex systems — computationally efficient, physically consistent, and operationally relevant.
Data-integrated models of physical systems. Real-time data enables enhanced monitoring, prediction, and operational awareness — from extreme weather to autonomous flight.
We fuse sensor, geospatial, and historical streams with predictive analytics into intuitive dashboards — actionable intelligence for complex environments.
Digital-twin solutions for next-generation manufacturing — including additive manufacturing for spacecraft — pairing predictive analytics with physics-based modeling for dramatic gains in efficiency and quality.
Data-driven modeling and physics-informed simulation for problems that defy traditional trials — sepsis, critical casualty care, and hemorrhagic shock.
A unified hybrid forecasting system for naval operations
A Julia framework that fuses fast global physics, SciML surrogates, and high-resolution simulation — generating near real-time environmental forecasts at sub-kilometer resolution for the tactical edge. Built on the Julia community’s open source ecosystem:
High-efficiency AI twins for modeling & prediction via surrogates
An open, GPU-optimized digital-twin framework in Julia that converts physics-based wildfire computations into deployable surrogate models — enabling faster-than-real-time propagation modeling for proactive response across the Colorado–Wyoming region.
A hybrid digital twin for space-grade metal additive manufacturing
Predictive, real-time defect prevention for metal AM — physics-informed neural networks fused with thermal-metallurgical models on the Julia SciML stack, driving toward sub-millisecond closed-loop control. Led by Rallypoint One with USC’s McNAIR Center.
Multi-scale cardiac modeling for trauma and hemorrhagic shock
A Julia digital-twin stack spanning single-cell electrophysiology, tissue propagation, and whole-body circulation — built to model cardiac response under battlefield trauma and hemorrhagic shock, on the open Julia cardiac-modeling ecosystem.
Whether you're a program office navigating acquisition or a partner with a mission-critical challenge — we'd like to connect.
Rallypoint has select opportunities for highly qualified experts who want to apply simulation, AI/ML, and predictive analytics to problems that matter. If you want to change the world with a great team, we want to connect.