I’ve been working on resonaX
— an experiment to see if we can simulate real B2B customers using AI.
The idea: instead of sending surveys or running A/B tests, what if marketers could ask questions directly to an AI twin of their ideal customer — built from real data like LinkedIn profiles, CRM notes, and behavioral insights?
Each twin captures that customer’s role, pain points, buying triggers, and communication style.
You can then ask:
“Would this headline make sense to you?”
“Why would you hesitate to book a demo?”
“What would make this offer more relevant?”
Under the hood:
LLMs + embedding models fine-tuned on buyer language
Real-world inputs (LinkedIn data, optional CSV uploads)
Lightweight feedback layer to validate responses
70+ beta testers are using it to test messaging and GTM ideas before launch.
Would love feedback from HN:
How might you improve the data ingestion layer?
How can I simulate a focus group?
How can i combine data to create a digital twin of a post like VP of Marketing (broad as some users are demanding not testing with just one profile but a combination of atleast 10)?
Any ideas to make the twin modeling more reliable over time?
Free beta: https://resonax.ai
Comments URL: https://news.ycombinator.com/item?id=45822964
Points: 1
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Source: resonax.ai
