AI Compute & Hardware

MEXT is radically lowering the cost of computing with our AI-powered predictive memory technology. Server memory (DRAM) is one of the biggest cost components in the data center, but it’s common to find that over half of the provisioned memory isn’t actively utilized by applications and can be considered cold. MEXT solves this utilization issue by offloading cold memory to a 20x lower-cost location—Flash—and leveraging AI to mitigate the effects of Flash latency. MEXT’s AI engine continually predicts which offloaded pages might by requested by the application, and transparently moves them back into DRAM before the requests are even made. As a result, the application stays performant because from its perspective, the relevant memory pages are already resident in DRAM. This empowers customers to run applications within a much smaller DRAM footprint—yielding substantially lower costs. On the other end of the spectrum, there may be customers whose applications are running out of memory and suffering performance issues as a result. In the past, these customers would have to either procure a larger system or shard their data across multiple smaller systems - both of which are complex and expensive paths. With MEXT, customers can cost-effectively and flexibly create a large memory system in a matter of minutes. MEXT is a patent-pending software-only solution that works with any configuration: on-premises or Cloud, with any processor, in virtualized / bare-metal / containerized environments, with no changes to the OS or applications. https://www.youtube.com/watch?v=zg-uBMsV_Yg

SwarmOne is an inference orchestration platform built for heterogeneous silicon- NVIDIA, AMD, Intel, and Groq - delivering the lowest cost per million tokens through dynamic prefill/decode disaggregation, SLO-driven autoscaling, and heterogeneous GPU packing. The result: 30% utilization becomes 90%+, TCO drops, and production inference finally runs the way it should.

MisaLabs builds containerized AI microservices that deploy on-prem, on AWS, OCI, or hybrid - with no data leaving the client environment. We work with two types of organizations: those with internal engineering teams who need production-grade AI building blocks, and those who want MisaLabs to act as their embedded AI engineering function. Our clients are typically in financial services, healthcare, and other regulated industries where data sovereignty and reliability are non-negotiable - though we work with other organizations looking to implement AI at scale.

The Problem: Your data is not ready for AI. Enterprises continue to struggle with taking models from proof of concept to production because some of their most valuable data—transactions, customer data, logs, sensor streams, images, and other real-time signals—cannot be moved to a centralized environment. Regulatory constraints, cost, latency, and operational risk make traditional data centralization strategies slow, expensive, and often impossible to fully achieve. As a result, AI adoption stalls at the exact moment organizations attempt to deploy models into mission-critical workflows. The solution: Don't move your data. Move your AI instead. Axonis is a new approach to deploying enterprise AI at scale without centralizing data. Instead of moving sensitive data, Axonis brings models, GenAI use cases, and agents directly to the data—securely and in place—enabling governed, production-grade AI at up to 75% lower cost and ~12× faster time-to-value than centralized architectures. The Axonis federated AI platform introduces a new architectural model that eliminates the need for data migration or duplication and delivers secure, immediate, and scalable AI for training, fine-tuning, and deploying models across cloud, on-prem, and edge environments. Axonis complements and protects existing cloud and data lake investments by providing a parallel path that enables organizations to act on raw, real-time data immediately, without slowing down or rethinking their centralization strategy.