RAG and MCP: The Tech Behind Learn Amp's AI

Remember my last post about building AI at Learn Amp? I promised to dive into the technical side and explain what RAG and MCP are. Well, here we go - no computer science degree required.

Why We're Not Training Our Own AI Model

Let me start with what we're NOT doing. We're not building our own AI model from scratch.

Here's why: training custom AI is like trying to recreate Google from your garage. It costs multiples of thousands, takes months of work from specialised engineers, and comes with inherent data privacy challenges.

Plus, there's a fundamental problem with L&D - every organisation has its own philosophy and approach. One-size-fits-all doesn't work when one company believes in direct, structured training while another emphasises peer learning and mentorship. Some organisations coach through regular one-on-ones, others prefer group workshops. A single AI model could force everyone into the same box.

And here's the kicker - I haven't spoken to a single customer who hasn't specifically asked us NOT to train models on their data. They want AI's benefits without their information being used for training. Can't blame them.

For us, the effort just doesn't make sense. The return on investment isn't there, especially when better solutions exist.

Enter RAG: AI That Actually Knows Your Stuff

RAG stands for Retrieval Augmented Generation. Think of it as giving AI a really good filing system instead of trying to cram everything into its brain.

Here's how it works in three simple steps:

Someone asks a question - A user wants to know about their learning program
AI searches your specific data - It looks through your documents and information
AI creates a custom answer - Based on what it found in YOUR system

The magic happens in step two. Our AI doesn't just look for exact matches—it understands meaning. Ask about "improving employee engagement" and it'll find relevant info even if your documents talk about "boosting team morale" or "increasing staff satisfaction."

Why RAG Changes Everything

This approach solves real problems:

No more hallucinations - When AI makes stuff up, that's called hallucinating. RAG dramatically reduces this because it checks facts in real documents instead of guessing.

Always current - The AI uses the newest information in your system, not outdated training data from months ago.

Affordable personalisation - Every customer gets answers based on their own data and processes, without us building expensive custom AI for each one.

Fast to implement - We can use existing AI (like GPT-4) and connect it to your data. This saves months of development and millions in costs.

MCP: The Universal Plug for AI

Next up is Model Context Protocol (MCP).

Think of MCP like a universal adapter for AI systems. Just as our data lake lets customers connect their BI tools to pull learning data, MCP will let them connect their own AI tools to Learn Amp.

This means in the future, your company's AI assistant could directly:

Create learning tasks
Build training content
Add users to programs
Pull learning analytics
And much more

This is huge for customers who've already invested in their own AI systems. Instead of having separate, disconnected tools, everything can work together seamlessly.

What This Means for You

These technologies tackle different challenges:

RAG powers our AI to give accurate, personalised answers based on your actual data - making Learn Amp's AI smarter and more reliable
MCP will let your own AI tools connect to Learn Amp - extending your existing AI investments into your learning platform

No thousand-pound AI training bills. No privacy nightmares. Just practical, powerful AI that works with your data and plays nicely with your other systems.

Looking Forward

This is just the beginning. As we roll out these technologies, you'll see AI in Learn Amp become more capable, more integrated, and more valuable to your organization.

Stay tuned for updates as we bring these features to life. And if you're curious about how this could transform your L&D operations, reach out. We'd love to show you what's possible.