Insights, updates, and perspectives on Data & AI
Bad data rarely crashes your pipeline. It flows straight through. Here is how Inferdat builds production-grade data pipelines on AWS, and what we can show you on your own data before a single dollar is committed to a full build.
An AI agent that can touch your CRM, your finance system, and the open web is only as trustworthy as the controls around what it can reach. Here is how Inferdat builds production-grade agentic AI on AWS, and what we can show you running before a build decision is made.
Most document automation projects look promising in a demo and fall apart in production. Blind extraction, no confidence scoring, no human review layer, and pipelines that collapse under real load. Here is what production-grade IDP actually requires, and how Inferdat has already built it.
Every RAG demo looks impressive over a handful of clean documents. The hard part is what happens after you deploy, when documents go stale, policies contradict each other, and nobody knows what state the knowledge base is actually in. Here is how Inferdat builds enterprise knowledge assistants that stay accurate, and what we can show you on your own documents before a build decision is made.
The biggest names in business intelligence, Tableau, Looker, and Power BI, were built for a different era of analytics. Here is what teams are switching to in 2026, and why flat pricing, AWS-native architecture, and real AI integration are becoming the new baseline.
Building a GenAI workload is the easy part. Running it reliably in production is where most organizations get stuck. Here are the three managed services partners best equipped to own that problem on your behalf.
