Tech insights from industry thought leaders

Stop building fragmented AI tools. Learn why an AI Orchestration Platform is the required system of control to mitigate Shadow AI risk, accelerate ROI, and future-proof your strategy with resilient, multi-model workflows.

Stop letting bad data foundations kill your AI projects. Learn about the common pitfalls in AI data storage, why your current data lake isn't enough, and how to build the scalable foundation necessary to move from prototype to reliable production.

AI is a data-first discipline. Its success is 100% dependent on the quality of the fuel it consumes. Learn the three most common data pitfalls that are pre-ordaining your AI projects to fail and outline a practical framework to get your data clean, connected, and "AI-ready."

The future of enterprise AI is a multi-agent system, a team of specialized agents that each have deep expertise. AI agent orchestration is where real value is realized, ensuring that team of agents is coordinated.

The pilot was a spectacular success. Your new AI tool is delivering the "wow" moments you hoped for, and adoption is climbing. The team is celebrating a breakthrough. But a few months later, a different kind of breakthrough happens: your cloud bill breaks through its forecast and lands, three times larger, in the CFO’s inbox. This isn't a sign of failure. It's a sign you've found something valuable. But it's also your entry into the new reality of AI unit economics.

Your users are asking harder questions. Questions that don’t live in a single document but require connecting dots across multiple sources. "What were the common themes in customer complaints for Project X, and how do they correlate with the engineering challenges we documented in Project Y?" So, how do you break through? The answer lies in a powerful architectural evolution called GraphRAG. It’s not just another buzzword; it’s the next logical step for any organization serious about building a true intelligence engine.

Too many teams treat AI like a lottery ticket, hoping for a magical win. The reality is that a successful AI implementation is a strategic construction project. It requires a clear blueprint, a solid foundation, and a disciplined plan for execution. Without that, you're not building a business asset; you're building an expensive science fair project.

The promise of AI-driven application modernization is intoxicating. Tools that can translate decades-old code, refactor monolithic systems, and slash project timelines by nearly half are no longer a distant dream; they are a present-day reality. For leaders staring down a mountain of technical debt, the temptation is to move fast, using AI to execute a rapid, “lift-and-shift” modernization. This approach, often called “paving the cow path,” focuses on updating the technology without fundamentally changing the underlying business process. But is it the right move?

The race to deploy generative AI is on, and the capabilities of new Large Language Models (LLMs) are captivating. But in the rush to launch the next chatbot or AI co-pilot, we see a critical conversation getting skipped. Everyone's focused on the model, but on the front lines, we know the real bottleneck, and the biggest opportunity for ROI, isn't the AI itself. It's the data architecture that feeds it.

The real conversation isn't about whether AI is "smarter" than automation. That's the wrong way to look at it. The choice is much more fundamental: Are you trying to perfect a process you already know, or are you trying to find answers in a sea of uncertainty? Get that right, and you'll make a smart investment.

The old "Buy vs. Build vs. Integrate" debate is dangerously outdated, and being radically rebalanced by a simple, undeniable truth we are seeing more and more every day: The traditional SaaS and COTS (Commercial Off-The-Shelf) software model is dying.

We get asked all of the time, "When should I switch from the basic ChatGPT interface to something more custom?" Check out our thoughts on how to know when you've outgrown the off-the-shelf tools.

Electronic Health Records (EHR) is an advancement from traditional, paper medical charts to a digital system

Retrieval Augmented Generation (RAG) is reshaping how developers work with large language models (LLMs)

Generative AI has revolutionized the way businesses operate

MorelandConnect Wins HealthTech of the Year Award for Their Software Empowering Maternal and Neonatal Health

The construction industry, while vital and expansive, has historically been slow to adopt new technologies.

Generative AI is at the forefront of everyone’s minds, offering businesses the potential to revolutionize operations, enhance productivity, and gain competitive advantages.

Reading about AI is insightful, but observing AI in action is even more enlightening.

Today’s online space is full of new and increasing dangers, putting data security top of mind for many businesses

Generative AI technologies are rapidly changing how businesses operate.

The Hidden Danger from a Missing Stop Sign in Waze

The manufacturing industry is facing a significant skilled labor shortage, impacting productivity and industry growth.

This expert review dives into a comparative analysis of Azure AI vs.