How Consulting Firms Can Scale Their Delivery Teams Without Sacrificing Quality
Imagine this.Your team wins a competitive bid with a marquee client. The strategy is sharp, the relationships are strong, and you’ve got the delivery team to back it up. But here’s the catch: this project is bigger than the usual scope, with more technical complexity...
Making Multi-Cloud and Edge Work in Practice: From Strategy to Execution
For most tech leaders, the decision to go multi-cloud or adopt edge computing isn’t about if, but how. The benefits are widely recognized: multi-cloud reduces vendor lock-in and offers pricing flexibility, while edge computing cuts latency and brings computing closer...
Key Trends Shaping Modern Data Teams
The Evolution of Modern Data Teams In the past, data teams were primarily composed of data analysts and IT professionals. However, as the importance of data has grown, so too has the complexity of the roles within these teams. Today, modern data teams are more...
The Nearshore Engineering Playbook: Insights for 2025 and Beyond
Engineering leaders today are facing a brutal equation: tighter budgets, scarce top-tier talent, and rising expectations for AI-driven products. The pressure to deliver more with less is real. Nearshore software development isn’t a new idea, but it’s evolved. Done...
Balance in Software Development
By Dario Ochoa, QA Engineer at Distillery I’ve been working as a QA for quite a few years, across projects of all kinds. Over time, I keep asking myself: Why do we need testing? Do we really need it? Am I providing value as a QA? Then I see video games crashing on...
Case Study: How Distillery and the Oakland Ballers Made Sports History With AI
When baseball met artificial intelligence, Distillery was behind the build. On September 6, 2025, the Oakland Ballers hosted the first-ever fully AI-managed professional baseball game. In a groundbreaking showcase, every strategic gametime decision, from lineups to...
From Chatbot to Assistant: What’s Next for Enterprise NLQ
Why “answering questions” isn’t enough In most enterprises, conversational AI starts with pilots. A chatbot can answer simple questions, summarize content, or provide quick insights. It’s a helpful step forward, but limited. At scale, teams don’t just need answers....
From Demo to Production: Making NLQ Enterprise-Ready
Why chatbot demos impress, but rarely scale For many enterprises, AI exploration begins with a proof-of-concept. An LLM queries a dataset in plain English, the answers look sharp, and the demo sparks excitement about what’s possible. But when the same approach is...