Multicloud AI & ERP / Agentic AI & Cloud AI Infrastructure
About
AI that takes actions, and the cloud AI infrastructure that runs it: agent platforms, MCP and agent-to-agent protocols, multi-agent orchestration, agent identity and governance, computer-use and coding agents, low-code builders, AI accelerators, inference hosting, large-scale training, cluster networking, MLOps, monitoring and FinOps for AI.
How NTS helps
NTS builds AI agents that act safely inside your systems, and the infrastructure under them: right-sized cloud GPU and AI accelerator capacity, efficient inference, MLOps pipelines and cost controls that keep AI spend predictable.
Each diagram compares how AWS, Azure and Google Cloud handle the same problem. Select Read more for the full diagram and write-up.
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Agent PlatformsWhere production AI agents run
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Tool Use, MCP & Agent-to-AgentHow agents reach tools and each other
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Multi-Agent OrchestrationTeams of agents with one coordinator
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Agent Memory, Identity & GovernanceWho an agent is, what it remembers, what it may do
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Browser & Computer-Use AgentsAgents that click, type and navigate
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AI Coding Assistants & Dev AgentsFrom autocomplete to autonomous pull requests
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Low-Code AI Builders & Workplace AgentsAgents built by business teams, governed by IT
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AI Chips & AcceleratorsGPUs, Trainium, Maia and TPUs compared
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Inference & Model HostingServing models fast, reliably and at a fair price
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Large-Scale TrainingThousands of accelerators, one training run
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AI Cluster NetworkingThe network between chips decides training speed
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MLOps & LLMOpsPipelines that make models reproducible
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Monitoring AI in ProductionQuality, latency and cost for every request
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FinOps for AIKeeping token and GPU spend under control
Need one of these on your cloud?
NTS designs, migrates and runs these architectures on AWS, Azure and Google Cloud. Most engagements start with a 30-minute architecture review.
- Phone
- 469-469-1965