WHY convert existing NLU based virtual agent topics to LLM based?

[Suggy]

We have around 500 NLU based virtual agent topics.

Customer is asking us to migrate all of them to LLM based topics.

I am not getting clarity on WHY to convert existing NLU based virtual agent topics to LLM based? What benefit will I get if I convert?

PS - Request you to reply only if you have experience/worked on this MIGRATION topic.

TIA!!!

[Matthew_13]

So when a customer asks to migrate all ~500 NLU topics, in my experience it’s almost never because every topic truly needs to be LLM-based really. It’s usually a signal that the NLU estate has become painful to manage.

I’ve seen this happen a few times now. Once you cross a few hundred topics, teams are spending more time maintaining intents than improving the Virtual Agent experience. Utterannce tuning overlap between intents retraining and missed matches become a constant background task. The migrate all 500 request is often really saying:
“We’re tired of babysitting NLU.”

Another big driver is discovery. With that many topics, users don’t phrase things the way the intents expect. Even well-built NLU models start to miss, and users hit fallback too often. Customers always hear that LLM-based routing handles natural language better and assume converting everything will fix discovery across the board.

There’s also usually topic sprawl if you know what I mean... In every large one Ive ever worked with only a fraction of the topics actually get meaningful traffic. The rest exist because they were added over time and never retired. LLM feels like a way to avoid cleaning that up.

That being said, when we actually implemented migrations, we never moved all topics at once. The Team and I focused on:

• High-volume, discovery-heavy topics

• Topics where NLU tuning was clearly not paying off

• Areas with lots of phrasing variability or multi-language usage

Highly deterministic flows like password resets simple catalog orders stayed on NLU initially because they were already working fine and didt gain much from LLM routing.

So when a customer pushes for 500, my response would be usually something like this:

“We can migrate a large number, but let’s be clear on the goal. In past implementations, migrating a smaller, targeted set delivered most of the value without the risk and effort of a full estate move.”

@Suggy - Please mark Accepted Solution and Thumbs Up if you found Helpful!!

[Its_Azar]

Hi there @Suggy

From hands-on migration experience, there is no inherent or technical requirement to convert existing, well-performing NLU-based Virtual Agent topics to LLM-based topics. NLU topics are deterministic, cost-effective, and easier to govern, which makes them ideal for high-volume, structured, and compliance-sensitive workflows. LLM-based topics add value mainly when there is a need to handle highly unstructured, free-form user input, reduce ongoing intent-training effort, or support more contextual and conversational interactions. Migrating all topics purely for modernization delivers limited ROI, introduces higher cost and governance complexity, and can reduce predictability. A hybrid approach—retaining NLU where it works

But as always try to explain the tradeoffs, but ultimately customer/client wins the argument haha