Thanks for your question! Uxia isn’t just raw LLM answers. We layer on:
Personas with goals/motivations so feedback is authentic.
Task simulations to mimic real tester workflows.
Consistency rules so a “designer” vs. “novice” behaves differently.
Aggregation to surface patterns across many synthetic users.
The LLM is the engine, but the structure around it makes the output closer to real user research than generic AI text. It’s not a full replacement for humans, but it’s fast, cheap, and great for early-stage insights.
Great question. Synthetic users are best for early iteration cycles: spotting usability friction, validating flows, stress-testing designs. They’re not a replacement for real human intuition (e.g. emotions, motivations). Our vision is that they complement human testing: use synthetic users to test 20 times during a sprint, then validate the final version with real humans.
Personas with goals/motivations so feedback is authentic.
Task simulations to mimic real tester workflows.
Consistency rules so a “designer” vs. “novice” behaves differently.
Aggregation to surface patterns across many synthetic users.
The LLM is the engine, but the structure around it makes the output closer to real user research than generic AI text. It’s not a full replacement for humans, but it’s fast, cheap, and great for early-stage insights.