New York-based Concertio recently closed its $4.2 million seed round, led by Differential Ventures. The company is planning to use the funds to scale operations of its AIOps Optimizer platform.
- Leveraging machine-learning technology, Concertio Optimizer enhances applications and systems to achieve maximum performance through the optimization of the myriad of configuration settings employed in these complex systems.
- Concertio Optimizer features continuous and static modes of optimization to tackle any parameter and resource tuning challenge enterprises face today.
- Concertio Optimizer products are used in a variety of use-cases, including maximizing system performance, reducing IT and cloud costs, Kubernetes resource optimization, and minimizing latencies in high-frequency trading platforms.
- Concertio features three modes of optimization: agent-based dynamic real-time optimization for use in production servers, continuous optimization where static optimization is implemented within the CI/CD pipeline, and static optimization for use by hardcore performance engineers and IT professionals.
- Intel, Marvell and Mellanox have each published use-cases with Concertio.
“We’re entering the era of self-tuning servers, where servers automatically adjust their settings dynamically in real-time according to the workloads that they run,” said Dr Tomer Morad, co-founder and CEO of Concertio. “Our Optimizer products transform general-purpose systems into high-performant special-purpose systems, thereby boosting performance and slashing infrastructure costs.”