“Can you lower the price? You’re just a ChatGPT wrapper, right?”
I woke up to an email from a prospect this morning that stopped me in my tracks.
They wanted a steep discount. Their logic? Since we use LLMs, we must just be a “wrapper.”
I had to be honest in my reply (see below 👇).
I told them: “I agree. ChatGPT wrappers should be cheaper. Also, you shouldn’t be using a ChatGPT wrapper.”
If you are looking for generic text generation, go for the cheapest option. But at Alhena.ai, we aren’t building a chatbot to chat about the weather or answer return policies (with a hyperlink). We are building a revenue engine.
There is a massive difference between a “wrapper” and a vertical AI solution.
A wrapper summarizes text. Alhena understands how to sell.
We do the gritty, unglamorous work that standard models can’t do out of the box:
✨ Building Product Taxonomy from your catalogue: So the AI knows a “serum” from a “toner.”
✨ Vertical Agents: Like Skin Analyzers, Routine Builders, and Shade Matchers.
✨ Driving Discovery: Proactively finding the right products for the customer, not just waiting for questions.
It’s the difference between:
❌ “Here is our return policy.” vs.
✅ “I see you’re looking at that jacket, did you know this scarf matches it perfectly?” (Upselling)
❌ “Search our catalog here.” vs.
✅ “Tell me who you’re shopping for, and I’ll find the exact right product for them in seconds.” (Discovery)
If you want a tool that just answers tickets, buy a wrapper. It should be cheap.
But if you want an innovation partner that drives upselling, conversion, and AOV? That requires real engineering, not just a prompt.
To AI Application companies, how do you handle the “wrapper” objection?