31–40 of 171 posts
As someone who's been doing AI call centres for a while, I'm not surprised. It's really, really hard to build voice AI that works. There are no open source solutions that work out of the box. But the biggest problem is ASR. WER is still atrocious even with SOTA models. When you add drug names and regional accents, it's a recipe for disaster.
Pharmacy phone lines are a terrible first use case for voice AI. Older callers, drug names, insurance mess, zero patience. Automating "store hours" is fine. Automating refill exceptions is how you get this outcome.
I just don't get why we're not doing it vertically like you said here. Implement a part of the cognitive work using AI but let the hard parts be done by a person. They're still gonna be more rich, just less so.
Pharmacy phone lines are a terrible first use case for voice AI. Older callers, drug names, insurance mess, zero patience. Automating "store hours" is fine. Automating refill exceptions is how you get this outcome.
Like they don’t even say the full name of the prescription they just tell you the first three letters and they’ll say “for the patient born on…”
Current pharmacy IT systems are currently almost 100% automated so how are you claiming it’s the first use?
So - I run a company that does AI agents for pharmacy. We are at Series B now and growing well - series C in 9-12 months given growth. We just acquired a competitor of that vendor so very much an insider. First, The technology works, and it scales, but the whole bottleneck is domain expertise and implementation. These are expensive, and hard to scale. We hire pharmacists as project managers, that's how important doma…
How happy are their patients?
As someone who's been doing AI call centres for a while, I'm not surprised. It's really, really hard to build voice AI that works. There are no open source solutions that work out of the box. But the biggest problem is ASR. WER is still atrocious even with SOTA models. When you add drug names and regional accents, it's a recipe for disaster.
WER = Word Error Rate
Too many acronyms; not everybody is in your field.
So - I run a company that does AI agents for pharmacy. We are at Series B now and growing well - series C in 9-12 months given growth. We just acquired a competitor of that vendor so very much an insider. First, The technology works, and it scales, but the whole bottleneck is domain expertise and implementation. These are expensive, and hard to scale. We hire pharmacists as project managers, that's how important doma…
This is such a great graph. Your company feels successful because your customer is happy yet the rest of the world would be just happy if your company died in a fire. This seems to also be just fine for companies like yours.
Companies will pawn off thier customers to AI at their peril. In many ways this is a repeat of the India call center train wrecks of the 00s. On paper, letting someone in Bangalore vs onshore handle incoming customer service calls looked like a path to amazing savings. In practice the customer experience was horrendous and companies CTRL-Zed these decisions and rapidly brought customer service back onshore again. AI…
So - I run a company that does AI agents for pharmacy. We are at Series B now and growing well - series C in 9-12 months given growth. We just acquired a competitor of that vendor so very much an insider. First, The technology works, and it scales, but the whole bottleneck is domain expertise and implementation. These are expensive, and hard to scale. We hire pharmacists as project managers, that's how important doma…
> We have hundreds of pharmacies with us now and they mostly successful and happy How happy are their patients?
As someone who's been doing AI call centres for a while, I'm not surprised. It's really, really hard to build voice AI that works. There are no open source solutions that work out of the box. But the biggest problem is ASR. WER is still atrocious even with SOTA models. When you add drug names and regional accents, it's a recipe for disaster.
Just curious, why are drug names such a disaster? Do LLMs not understand pronunciation keys?