Next-Level Optimization with Rose
We believe your biggest decisions shouldn’t be limited by solver performance.
That’s why we’re building Rose—a high-performance, parallel optimization solver for solving large-scale mixed-integer programming (MIP) problems. Rose handles real-world complexity at scale by parallelizing the entire solving process—not just LP relaxations, but branching, cuts, and heuristics—across CPUs and GPUs including NVIDIA Grace Hopper pods. The result: faster solve times, larger models, and better decisions with fewer tradeoffs.
Rose isn’t just faster—it’s smarter and more efficient, transforming previously intractable problems into solvable challenges. The powerful combination of Rose and high-performance computing enables enterprises to:
- Solve larger, more complex optimization problems
- Achieve dramatic reductions in solve times
- Realize ROI that significantly exceeds infrastructure costs
Enterprise-Ready, Seamlessly Deployable
Enterprise-Ready, Seamlessly DeployableWith a user-friendly interface and flexible architecture, Rose runs as a service, streamlining setup, integration, and scaling. It abstracts away the mathematical complexity, enabling engineering, operations, and data science teams to rapidly deploy and gain value—without needing to be experts in the underlying math.
Even organizations already performing optimization will find new value with Rose. Its distributed architecture and parallel capabilities dramatically outperform traditional solvers, unlocking a new tier of performance and capability.
Performance that Translates into Profit
Performance that Translates into ProfitSimpleRose offers a compelling business advantage: maximum ROI through high-speed, high-efficiency computing.
By dramatically accelerating solve times and expanding the solvable problem space, Rose allows organizations can make faster, better-informed decisions—transforming optimization into a powerful engine of profitability that far exceeds infrastructure costs.