Modular Cloud

MAX is Modular’s open and extensible AI inference framework for building and serving models. It supports thousands of model architectures across image, video, speech, and text modalities, exposes OpenAI-compatible endpoints, and can program deployments across multiple GPUs, nodes, and mixed hardware. MAX is part of Modular’s unified stack alongside Mojo, the company’s Pythonic systems language for CPUs, GPUs, and ASICs; Modular describes MAX as providing portable model serving and performance across different hardware platforms.

The Modular Platform is an open-source platform for AI development and deployment, comprising the MAX Framework and the Mojo programming language. Its repository includes the Mojo compiler and standard library, MAX accelerator libraries and kernels, Python-based model pipelines, code examples, and an OpenAI-compatible MAX inference server. The platform supports model serving and AI development while retaining Python-based workflows. The repository is licensed under the Apache License 2.0 with LLVM Exceptions, while MAX usage and distribution are licensed under the Modular Community License.

Gimlet Cloud is Gimlet Labs' serverless inference platform for AI agents and multi-agent systems. It can run agentic pipelines with custom logic, data sources, chained models, and non-model stages such as search; the platform manages scheduling, orchestration, and optimization. Its multi-silicon approach splits inference workloads into fine-grained pieces and maps them to suitable hardware, including Nvidia, AMD, AWS Trainium, Cerebras, D-Matrix, and Intel Gaudi systems. Gimlet describes this heterogeneous execution model as achieving 3–10× faster inference than homogeneous systems. The company also develops kforge, a multi-agent system that generates and checks optimized low-level kernels from PyTorch for CUDA, ROCm, and Metal backends.

Crusoe Cloud is Crusoe's cloud infrastructure platform for AI workloads, providing compute, storage, networking, GPU node pools, and a console for managing and observing GPU infrastructure. Crusoe describes its offering as AI infrastructure and cloud compute with an energy-first approach. Its Managed Slurm runs on Kubernetes: Slurm provides gang scheduling, topology awareness, and familiar sbatch workflows, while Kubernetes supplies dynamic resource management, node health handling, and observability. The platform's AutoClusters can notify operators, drain and replace a failed GPU node, requeue the workload, and resume training from a checkpoint without manual intervention; the demonstrations also cover sharing GPUs between training and inference as demand changes.

Gimlet Labs is an applied research lab and AI-infrastructure company building systems for serving AI workloads. Its Gimlet Cloud provides serverless inference for AI agents, supporting multi-agent systems, custom logic and data sources, model chains with non-model stages such as search, and platform-managed scheduling, orchestration and optimization. The company describes a multi-silicon inference architecture that divides workloads into fine-grained pieces and maps them to suitable hardware, including GPUs and specialized accelerators. Its research also covers workload partitioning, heterogeneous-hardware compilation, dynamic datacenter scheduling, hybrid edge/cloud execution and cost-aware optimization. KForge is its multi-agent system for generating optimized low-level kernels directly from PyTorch, with correctness checks and support for CUDA, ROCm and Metal backends.