Enterprise platforms. Performance advantage.
NVIDIA simulation, industrial digital twins and deployment engineering connected to high-impact AI programmes.
NVIDIA Isaac Sim engineering
Physics-based virtual robot tasks and synthetic observations. Task environments, sensor context and validation scenarios.
Take a closer lookNVIDIA Omniverse engineering
Industrial 3D and OpenUSD-based virtual environments. Engineering assets, equipment context and integration boundaries.
NVIDIA TensorRT engineering
Optimised inference engine development. Model-to-engine conversion and hardware-specific task quality.
NVIDIA Isaac Lab engineering
Robot learning and policy assessment across controlled environments. Policy training tasks and representative embodied evaluation.
ABB industrial robots engineering
Industrial robot workcell integration. Production tasks, robot programmes and equipment interfaces.
ABB RobotStudio engineering
Offline robot programming and workcell simulation. Robot programmes and virtual-to-controller correspondence.
AG UI Protocol engineering
Agent-to-interface interaction workflows. Task state and user-visible execution feedback.
Agent evaluation and execution tools
Task evidence, execution boundaries and meaningful quality assessment around agent workflows.
Agent2Agent Protocol engineering
Interoperability across agent applications. Accountable task exchange and specialist workflow handoffs.
Agility Robotics Digit engineering
Humanoid logistics and physical-task integration. Selected task environments and integration boundaries.
Airbyte engineering
Source integration and data movement workflows. Selected connectors, source meaning and processing ownership.
Alation engineering
Enterprise data catalogue and information governance. Source ownership, definitions and useful data discovery.
Amazon Bedrock AgentCore engineering
Enterprise agent runtime and operating services. Task execution, identity, tools and operational evidence.
Amazon Bedrock engineering
Managed model access and enterprise AI integration. Selected models, information boundaries and useful application behaviour.
Amazon EC2 GPU engineering
GPU compute for training and inference workloads. Hardware selection and complete workload performance requirements.
Amazon ECS engineering
Managed container workload execution. Application packaging and defined operating dependencies.
Amazon EKS engineering
Managed Kubernetes application environments. Enterprise workload resources, identity and service operation.
Amazon Kinesis engineering
Managed event and streaming data workflows. Event delivery and operational processing requirements.
Amazon Lambda engineering
Event-driven application and integration execution. Task interfaces and operating limits around the selected workflow.
Amazon Redshift engineering
Managed enterprise analytical data workloads. Warehouse integration and workload-specific data assessment.
Amazon S3 engineering
Object data and artefact storage workflows. Model releases, source data and information-access boundaries.
Amazon SageMaker AI engineering
Model development and managed machine-learning workloads. Training, artefacts and production release boundaries.
AMD ROCm engineering
GPU compute and model workload integration. Selected hardware compatibility and workload assessment.
AMD Versal engineering
Adaptive compute and embedded application integration. Hardware-aware task processing and deployment boundaries.
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