Foundational AI models continue to improve, but differentiation will ⬇️
Real battleground? AI agents that
✅ Have early-mover advantage / unique data access
✅ Integrate w existing workflows
✅ Offer an exceptional UX

It’s not about the model. It’s about the best product 🔥 #AI #product #LLM

Traditional tools like Zendesk can take 4 hours 😱 to build a single workflow for AI support automation. But what if you didn’t need workflows? With procedural AI, you can train agents to follow instructions in plain English—in just 10 minutes. Ready for the future of support? 🤖

The customer operations domain is like an iceberg 🧊: visible part (25%) is frontline support, while the hidden 75% is manual, repetitive back-office tasks 🛠️. They're deeply connected & ripe for transformation. Unlocking automation can redefine efficiency & customer experience #AI #CustomerSupport

Companies launch customer support automation and see close to 0 savings in FTE. Why? 🤔 Automating simple tickets, that take minutes for humans to respond, doesn't move the needle. Value lies in AI capable of handling complex, nuanced cases—going beyond the HC articles 🤖

When humans mess up it's one thing. When AI fails, it's a COMPLETELY different matter.
#1 question our clients ask ➡️ How do you ensure your AI doesn't f*** up?

Basic LLMs+RAG agents are risky. Our vision: AI CX agents that handle chats end-to-end. This requires more than basic training on your KB

🚀 Building truly superhuman AI support agents is about enabling them to understand. While RAG (Retrieval Augmented Generation) helps avoid hallucinations, real-world customer support is far messier. Let’s dive into how AI must evolve to deliver magical support experiences. 🧵