“What you are building is absolutely massive. This is a breakthrough for people wanting to validate an idea, look at how to solve a problem and accelerate the validation of hypotheses.”
Henrick Farías
Founding Team @Jeeves | Fintech
User research.
Without the
headaches.
Run your user and market research
with the most human-like AI participants.
Setup in seconds
Enterprise and Agency ready
Own your insights
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Trusted by
Install your Synthetic Users
Insight always available from within the company
The world’s most powerful in-depth interviews
Synthetic Users uses the most advanced AI architecture to create accurate synthetic interviews
In depth interviews
Surveys with global reach
Proprietary Data
You can probe deeper with every interview, ask more questions (for as long as you would like) and generate insights report.
Annotate and share with your team.
Run quantitative research at a massive scale in minutes. Thousands of surveys and quick insight.
Alternate between interviews and surveys for maximum insights.
With RAG you’re able to enrich your Synthetic Users and make them truly yours. This way you make your Synthetic Users much more unique.
As seen in
A complete suite based on your research needs
4 types of interviews
Interview type 3
Problem Exploration
interview
You wish to explore the pains and needs of an audience as you look for opportunities.
Interview type 4
Concept Testing
interview
You wish to explore the pains and needs of an audience as you look for opportunities.
Enrich your own Synthetic Users
You have proprietary data that will set your Synthetic Users apart.
Research Goal
interview
Set your research goal and let our multi-agent architecture drive your interviews.
Interview type 2
Custom Script
interview
Use your own questions (up to 10).
Prisma
Multi-study
Research
Planner
Run multiple studies at the same time and find concept fit.
“What you are building will radically democratize access to qualitative research within companies.”
Johan Van Langendonck
Director of Strategy
Data showing
effectiveness
At the end of the day it’s all about Synthetic Organic parity. We’re very open about how we measure it and improve on it.
Your questions, answered
The questions we get all the time and that we are happy to respond in detail below.
How does it work?
Synthetic Users uses the power of LLMs to generate users that have very high Synthetic Organic Parity. We start by generating a personality profile for each user, very much like a reptilian brain around which we reconstruct its personality. It’s a reconstruction because we are relying on the billions of parameters that LLMs have at their disposal.
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Once the personality profiles are established, these Synthetic Users are set in motion to interact in a simulated environment. Leveraging multi-agent frameworks, these users engage in conversations, make decisions, and evolve over time based on their interactions. This dynamic interplay allows for a rich and diverse set of behaviors to emerge, closely mimicking the complexity and unpredictability of real human interactions. The continuous learning and adaptation of these users ensure that the generated data remains relevant and reflective of nuanced human behaviors, providing valuable insights for various applications.
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What are the data sources
1. GPT, LLaMA, Mistral... we are agnostic re foundation model and will use the most appropriate for the task at hand. There are different levels of bias.
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2. With RAG you are able to upload your own proprietary data, which will add a level of granularity to your Synthetic Users and study that you may require.
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3. Just like with organic conversations, your level of specificity in your inputs will define the output. It’s really down to you.
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Synthetic Users vs ChatGPT
Yes, you can run the same questions on ChatGPT, but the results will be very different. We rely on an agentic architecture and therefore what you get is a whole bunch of agents talking to each other in order to fulfil the task at hand. We also use more than just one model and that adds to the diversity we are known for.
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In addition to the multi-agent architecture, Synthetic Users also benefit from enhanced contextual understanding and continuity in interactions. While GPT may provide coherent responses to isolated queries, Synthetic Users can maintain context across multiple interactions, enabling deeper and more consistent engagement. This capability allows for the simulation of long-term behaviors and relationships, offering a more holistic view of user dynamics. The incorporation of various foundation models and proprietary data further ensures that Synthetic Users deliver more accurate and contextually rich outputs, making them a superior choice for complex and specific use cases.
Loved
and trusted by the best
A small selection of what leaders, makers and builders have said about us.
“I just tried your product and I’m honestly scared. This reminded me of an episode of black mirror.”
Diego Jorge
Product Manager @TopTotal
“What you are building will radically democratize access to qualitative research within companies.”
Johan Van Langendonck
Director of Strategy, M&A and Partnerships at Bridgestone Mobility Solutions
“Oh! And I'm also someone who's used Synthetic Users to give me starting intelligence to then go and confirm that feedback with real life people. And guess what? The AI feedback lined up with human feedback over 95% of the time.”
Adam King
Behaviours Scientist
“If you’ve loved Synthetic Users, send us message on Twitter or Discord. We are building it with you!”
Your users aren’t AI super-intelligent
They’re human, with cognitive quirks and kinks. We replicate humans.
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