Linode

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.

Akamai LKE is the Kubernetes environment used in the workshop to run inference workloads on dedicated GPU nodes. It provides the namespace and deployment structure for a Jupyter notebook and a vLLM endpoint, and supports changing model-serving deployments and evaluating their latency, throughput, memory use, and output quality.

Google's cloud computing platform, providing AI and cloud computing services for security, data management, and hybrid and multicloud environments. In the cited video, GCP is discussed as a source of rented GPU spot instances when a company’s owned or contracted capacity is insufficient.

Higgsfield is an open-source GPU workload manager and machine-learning framework for training models ranging from billions to trillions of parameters, including large language models. It allocates exclusive or non-exclusive access to nodes, queues experiments to manage resource contention, and provides interfaces for distributed training with DeepSpeed ZeRO-3 and PyTorch fully sharded data parallelism. Its framework supports initiating, running, monitoring, and checkpointing experiments on allocated nodes, while its LLM training API includes model, data-loader, and experiment components. Higgsfield integrates with GitHub and GitHub Actions to generate deployment and run workflows: required tools and project deployment keys are installed on servers, code is deployed to configured nodes, and experiments are launched and monitored through GitHub. The repository describes compatibility with Ubuntu nodes offering SSH access and passwordless sudo, and reports testing with Azure, LambdaLabs, and FluidStack.

Ollama is a software platform for running and serving open models, including as a local model runtime for tasks such as resume evaluation, tagging, and summarization. Its website describes integrations with coding agents and other workflows, allowing users to launch tools such as Claude Code, Codex, OpenCode, and VS Code while switching models without changing the workflow. Local runs remain on the user's machine, while Ollama also offers hosted cloud models. The service states that prompts are not tracked or used for training by providers, and that its open-source software and open model support are intended to keep data private while automating work.