Picture this: You’re a U.S. CTO with a product roadmap that’s bursting at the seams. You’ve finally found the AI engineer who could take your platform to the next level — but bringing them in on an H-1B visa now costs $100,000 per petition (effective September 21, 2025).
AI isn’t just for Silicon Valley giants anymore. This is the story of how a mid-sized logistics company used practical AI tools — not hype — to solve real operational pain points and scale their business without hiring dozens of new people.
In 2025, every company is a tech company. Whether you’re selling shoes, managing supply chains, or running a digital healthcare platform — your ability to move fast, launch great software, and scale with confidence directly impacts your bottom line.
If you’ve ever heard the terms Artificial Intelligence (AI) and Machine Learning (ML) thrown around, you’re not alone. These two concepts are often used interchangeably, but they’re actually quite different. In this post, we’re going to break down what AI and ML really are, how they work, and why it’s important to know the difference.
In today’s fast-paced, technology-driven world, digital transformation isn’t just a nice-to-have; it’s what separates thriving businesses from struggling ones. Companies are pouring resources into software development and new technologies to stay competitive, work smarter, and deliver better customer experiences. But what’s the real payoff?
