Unikie as your partner for AI-assisted optimization
In today’s rapidly evolving tech industry, software performance optimization is crucial to ensure applications can meet the growing demands for efficiency, scalability, and developer productivity across various devices and platforms.
At Unikie, we help engineering teams optimize GPU and AI workloads. We’ve already seen strong results reducing execution time and energy use in AI/compute-heavy environments.
Consistent gains
AI-optimized code reduces GPU/accelerator execution time by 2–10×, depending on workload.
Energy efficiency
Up to 40% lower active power use, reducing datacenter TCO and extending device battery life.
Robust under constraints
Optimized kernels run successfully where baseline builds failed due to memory or timing bottlenecks.
Unlocking efficiency, scalability & productivity
At Unikie, we have developed a human-in-the-loop system with AI-driven workflows to accelerate AI and compute workloads, and to ensure peak performance across demanding applications.
Our AI-assisted workflow enhances responsiveness in latency-sensitive tasks, as well as consistently outperforms standard compilers and tool chains without the need for manual, low-level tuning.
Our optimization approach is already proving valuable for companies in cloud, semiconductors, automotive, and HPC, helping them cut costs and improve workload efficiency.
Cycle & Energy Reduction
Critical loops use up to 90% less GPU/CPU cycles, cutting data center costs and extending device runtime.
Predictable Latency
Faster, more reliable performance for AI inference, graphics rendering, and real-time perception workloads.
Lean Execution
Reduced memory allocations and kernel overhead for improved stability in large-scale AI and HPC environments.
Scalability
Same methodology effective across GPU generations and CPUs/NPUs, without manual retuning.
AI-based Performance Optimization for Image Processing
Webinar: AI-assisted Software Engineering
In this webinar, experts from Unikie and Grundium share their best practices, and you will learn more about optimizing algorithms leveraging problem-specific parameters to surpass the performance of state-of-the-art general approaches.
