Comuvia Tech
AI and technology choices, explained through decision trees.
Technology decisions you can follow
Comuvia Tech explains AI platforms, agents, infrastructure and data systems through concise videos and companion articles. One precise graph stays visible while a speaking presenter follows its branches and highlights the relevant blocks. Watch a short video, follow the text decision tree, and check the original sources. Videos use AI-generated narration and a synthetic presenter.
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Microsoft AI and Copilot: which layer do you need?
Microsoft · available on YouTube
A decision tree for embedded Copilots, low-code agents, custom AI, prebuilt APIs, classic ML and local inference.
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Microsoft AI and Azure
Building AI on Azure: which platform?
Microsoft
Choose between existing Copilot features, local inference, prebuilt AI services, Azure Machine Learning and Microsoft Foundry.
Watch and read the decision tree →Microsoft Foundry: deployment decision tree
Microsoft
Choose deployment geography, capacity, model source and tuning after selecting Microsoft Foundry.
Watch and read the decision tree →Azure RAG and agents: who owns the runtime?
Microsoft
Choose between Microsoft 365 agents, Copilot Studio, Foundry Agent Service and hosting your own agent code.
Watch and read the decision tree →Fabric, Synapse or Databricks: which data platform?
Microsoft
A decision tree to choose between Fabric, Synapse and Databricks.
Watch and read the decision tree →Entra, Defender or Sentinel: which security layer?
Microsoft
A decision tree to choose the Microsoft security layers you need.
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NVIDIA AI
NVIDIA inference: choose the serving layers
NVIDIA
Match NIM, Dynamo-Triton, TensorRT-LLM and Dynamo to your model packaging, optimization and serving needs.
Watch and read the decision tree →NVIDIA AI: RAG, fine-tuning or both?
NVIDIA
Distinguish knowledge gaps from model behavior problems before choosing retrieval, fine-tuning or both.
Watch and read the decision tree →GPU compute: own, rent or use managed capacity?
NVIDIA
A decision tree to choose how to source GPU compute.
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Databricks AI and analytics
Databricks Mosaic AI or an external AI platform?
Databricks
Decide which parts of an AI platform belong beside governed data and which can stay in external services.
Watch and read the decision tree →Databricks Genie, dashboards or existing BI?
Databricks
Choose conversational analytics, recurring dashboards or an existing BI layer, with clear definitions and permissions.
Watch and read the decision tree →Databricks AI: serving, search and agent components
Databricks
Choose model serving, AI Search and agent components while keeping identity, retrieval and runtime boundaries clear.
Watch and read the decision tree →Unity Catalog: where should governance live?
Databricks
A decision tree to choose a governance boundary for Unity Catalog.
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AI architecture and agent patterns
AI architecture: retrieve, tune or train?
AI Architecture
A decision tree to choose between prompting, retrieval, tuning and training.
Watch and read the decision tree →AI agents: when do you need durable orchestration?
AI Architecture
A decision tree to choose an orchestration and state model for an AI agent.
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Security operations and architecture
Security architecture: which control layer is missing?
SecOps
A decision tree to identify the missing security control layer.
Watch and read the decision tree →SIEM, SOAR, XDR, EDR and AIDR: what do you need?
SecOps
A decision tree to understand SIEM, SOAR, XDR, EDR and AIDR.
Watch and read the decision tree →SOC workflow: how does an alert become a response?
SecOps
A decision tree to follow an alert through the SOC workflow.
Watch and read the decision tree →Detection engineering: how do you build reliable detections?
SecOps
A decision tree to understand the detection engineering lifecycle.
Watch and read the decision tree →