Simor Consulting
Category: Operations
The case for streaming is straightforward: data that arrives in minutes instead of hours enables decisions that were previously impossible. Fraud detection catches transactions before they clear. Pers
LLM inference costs follow a pattern that catches teams off guard. The first prototype costs almost nothing -- a few hundred dollars a month during development. The pilot scales to a few thousand. Pro
Most data quality initiatives fail not because teams lack tools, but because they measure the wrong things. Teams track hundreds of data quality metrics, generate dashboards full of green indicators,
Prompt management in most AI teams starts the same way. One engineer writes a prompt, it works well enough, and the prompt gets committed to a config file. Three months later, there are forty prompts
Every AI infrastructure team eventually faces the same argument. One faction wants to build a custom solution because the commercial options do not handle their specific requirements. The other factio
Most vector database selection failures come down to one mistake: picking the technology before mapping the workload. Teams benchmark embedding search speed on a curated dataset, pick the fastest opti