
MCP Servers and Tools: How LLMs Connect to the Real World
MCP servers standardize how LLMs discover and use tools. This guide explains what they are, why they matter, how we use them at Blits.ai, and where the ecosystem is heading.











CTO & Co-Founder
Technical mastermind behind Blits.ai with over a decade of experience in AI and software engineering. Len saw the potential of conversational AI before it became mainstream.
Len is the technical mastermind behind Blits.ai. With over a decade of experience in AI and software engineering, he saw the potential of conversational AI before it became mainstream.
As CTO, Len has architected the Blits.ai platform from the ground up with enterprise requirements at its core. His deep understanding of machine learning, NLU, and AI security has been instrumental in securing partnerships with major financial institutions and international corporations.
"The honest part is that building enterprise AI isn't just about technical capability, it's about understanding business strategy and customer dynamics."
Len's vision for Blits.ai was born from frustration. While working at a global consulting firm in 2018, he witnessed firsthand how large enterprises were spending millions on chatbot solutions, only to end up disappointed. The technology wasn't living up to the hype, and businesses were left with rigid, underwhelming systems that couldn't adapt to their needs.
But Len saw something different. While experimenting with IBM Watson's API, he recognized the true potential of conversational AI. The world was changing. The way humans would interact with computers was about to fundamentally shift, from clicking buttons to having natural conversations.
"We're going to talk to our computers, not just click through menus."
This realization sparked the idea for Blits.ai, a platform designed to give large enterprises the control, flexibility, and power they needed to build truly effective conversational AI solutions.
Insights on AI, enterprise technology, and building conversational AI solutions

MCP servers standardize how LLMs discover and use tools. This guide explains what they are, why they matter, how we use them at Blits.ai, and where the ecosystem is heading.

Why commerce as we know it does not work for AI and what the Universal Commerce Protocol is trying to fix

Why giving AI agents controlled access to payments changes everything. The question is who designs the rules under which it does.

In the first week of January we turned quality assurance into a Bug Hunt Game. Here’s what happened when we put Hunters, Fixers, and a Judge on a shared leaderboard powered by Azure DevOps.

In my previous article 9 Things I Really Hate About AI, I mentioned how everyone suddenly seems to be an AI expert and how that creates a lot of noise. In the next few posts, I'll break down some key AI concepts specifically for business professionals. Why? Because even if you're actively looking for information, much of what's out there is either inaccurate or way too technical for the average manager to make sense of.

Let's be honest: I think it's great that technology is so embedded in our daily lives. It helps us get knowledge faster, complete tasks more efficiently, gives us inspiration, and occasionally scares the hell out of us with those crazy (fake) videos. I help a lot of companies implement AI, so in the end—it pays my bills. But after spending a ridiculous amount of time with all these new technologies, I feel it's time to reflect on the things I really hate about AI.

In the world of AI, where innovation moves at breakneck speed, being the CTO of a fast-growing scale-up is an exhilarating job—but not for the faint of heart. Our company specializes in large language models (LLMs), chatbots, digital humans, and voicebots, and we serve mainly large banks, international companies, and professional enterprises.

Someone once told me, stupid questions don't exist. This might be true, but people are still afraid to look stupid by asking questions that are assumed to be general knowledge. We are currently at a point in time, where most people are assumed to know what is meant by the term Artificial Intelligence (AI) and how it works, but less is further from the truth. With the recent boost of generative AI services like ChatGPT and Midjourney, the spark is ever more lit, everyone loves to talk about it but I only know a hand full of people who actually know how it works.

Over 5 years ago I started a chatbot (ad)venture called Blits.ai because I believed the way we as humans interact with data will change to a more conversation-based approach. With the current ChatGPT hype (generative AI), more and more people are coming to the same conclusion which is great, but we are not clearly there yet.

At Blits.ai we're introducing a new method that reshapes how chatbots work. From the beginning, our company has been focusing on building a chatbot ecosystem that gives companies access to the best performing engines of the market. Our current offering is both a middleware layer and a low-code software platform, that gives our customers access to 40+ cognitive AI services.

Building effective chatbots requires more than just basic conversation capabilities. Here are 15 advanced features that can transform your chatbot from a simple Q&A tool into a powerful business asset.