Why We Built Synthicant: The User Research Problem Nobody Talks About
Every product team knows the drill. You need user feedback before shipping a feature. So you open your calendar, send out recruiting emails, offer $75 gift cards, wait two weeks for scheduling, deal with three no-shows, and finally sit down with five people who may or may not represent your actual customer base.
By the time you have usable insights, your sprint is over and the feature shipped anyway.
This is the user research problem nobody talks about: the feedback loop is too slow for how fast modern teams need to move.
The gap between research and reality
I spent years watching this pattern repeat across product teams. The research team would produce a beautiful insights deck two months after the question was asked. By then, the product had moved on. The insights were academically interesting but operationally useless.
The teams that moved fastest weren't the ones doing the most research. They were the ones making the best guesses. And guessing, even educated guessing, is not a strategy.
What if you could interview users that don't exist yet?
The idea behind Synthicant started with a simple question: what if you could create a realistic representation of your target customer and interview them in real-time?
Not a chatbot with a personality prompt. Not a survey with branching logic. A psychologically modeled persona grounded in real customer data that pushes back, has biases, and responds like a real human would.
That's what Synthicant does.
How it works
You build a persona in one of two ways:
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Manual creation — Set personality traits using the OCEAN (Big Five) psychological framework. Adjust openness, conscientiousness, extraversion, agreeableness, and neuroticism on sliders. Add cognitive biases like "price-sensitive" or "skeptical of new technology."
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Dynamic creation — Upload real customer data: interview transcripts, support tickets, product reviews, even audio and video. The AI extracts personality traits, speaking patterns, beliefs, and biases automatically.
Then you interview them. In real-time. With streaming responses that feel like a conversation, not a form submission.
Why OCEAN and not vibes
We chose the OCEAN personality model because it's the most validated framework in personality psychology, with decades of peer-reviewed research supporting its predictive power. When you set a persona's neuroticism to 8/10, you're not just adding flavor text. You're activating a model that predicts real behavioral patterns: risk aversion, emotional reactivity, decision paralysis.
This matters because generic AI chat is terrible at simulating disagreement. LLMs are trained to be helpful. They want to agree with you. A well-modeled persona fights that tendency with principled pushback grounded in personality science.
Privacy is not optional
When you upload customer data to Synthicant, it passes through Microsoft Presidio for PII redaction before it ever reaches the AI or our vector database. Names, emails, phone numbers, and other sensitive data are stripped automatically.
This isn't a feature we added after launch. It was a design constraint from day one. If you're uploading real customer interviews, the AI should never see unprotected personal information.
The bottom line
Synthicant doesn't replace talking to real users. Nothing does. But it fills the gap between "we should talk to customers" and "we have time and budget to talk to customers."
You can run 50 synthetic interviews in the time it takes to schedule one real one. You can test pricing pages, landing page copy, and feature concepts against realistic personas before spending a dollar on development.
That's why we built it. Not to replace user research, but to make it fast enough to actually use.
Synthicant is in early access. Start your 14-day free trial and run your first synthetic interview in under 10 minutes.