Your CFO approved a budget for an AI initiative. Your CIO bought GPUs to run inference. Your CTO installed the servers in the same data center where your ERP runs. Three months…
When a data center moves from running inference or general workloads to training large AI models, the design assumptions you had stop working. Rack density multiplies, payload times change, and consumption peaks…
When you have a training cluster with 8, 16, or 64 GPUs, the network between GPUs becomes the immediate bottleneck. The choice between InfiniBand and 800G Ethernet affects latency, throughput, cost, and…
Your company wants to use an LLM with its own documentation. The typical conversation starts with ‘we need to fine-tune the model with our data’ and ends 6 months and $200k USD…
If your operation handles personal data of Mexican clients, financial data regulated by the CNBV, or any information that must remain on national territory by law, the question is no longer whether…
Where your data physically lives when you go to the cloud When your CFO asks 'where are our data actually?', the short answer in 2026 is: all three hyperscalers have physical presence…
Should your next enterprise network decision be SD-WAN or MPLS? The short answer: it depends on how many sites you have, what SLA you need, and how much monthly recurring cost matters…
Can AI be applied to the Mexican notarial process without breaking the rigor that the notarial act requires? Yes, but with respect for the process and clear limits on what the model…
Data sovereignty in the era of artificial intelligence is no longer a regulatory argument and has become a concrete operational constraint: the LLM (Large Language Model) providers that dominate the global market…
Can a small Mexican contractor participate in a hyperscale project? The answer is yes, but not where most people think. The value chain of a hyperscale project has many links, and each…
