What is Synthetic Users?
Synthetic Users employs cutting-edge AI architecture to create highly accurate synthetic interviews and surveys, enabling organizations to conduct comprehensive user and market research at scale. The platform leverages multiple foundation models and multi-agent frameworks to generate dynamic, human-like interactions that provide valuable insights for product development and market analysis.
The platform offers four distinct interview types including Problem Exploration, Concept Testing, Research Goal, and Custom Script interviews. With capabilities for both qualitative and quantitative research, users can conduct in-depth interviews, run large-scale surveys, and enrich synthetic users with proprietary data through RAG (Retrieval-Augmented Generation) technology.
Features
- Multi-Agent Architecture: Advanced AI framework for realistic user simulation
- Interview Types: Four specialized interview formats for different research needs
- RAG Integration: Capability to enrich synthetic users with proprietary data
- Global Scale: Ability to conduct thousands of surveys in minutes
- Follow-up Tools: Deep-dive capabilities with extended questioning options
- Insight Generation: Automated research reports and annotations
Use Cases
- Problem and need identification research
- Concept and messaging testing
- Market gap analysis
- Product lifecycle optimization
- User behavior analysis
- Market expansion research
- User satisfaction assessment
- Product adoption studies
FAQs
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How does Synthetic Users work?
Synthetic Users generates personality profiles using LLMs, then sets these synthetic users in motion within a simulated environment using multi-agent frameworks. These users engage in conversations, make decisions, and evolve based on interactions, creating realistic human-like behaviors. -
What are the data sources used by Synthetic Users?
The platform uses various foundation models including GPT, LLaMA, and Mistral, allows integration of proprietary data through RAG, and generates outputs based on the specificity of user inputs. -
How is Synthetic Users different from ChatGPT?
Synthetic Users uses an agentic architecture with multiple AI models talking to each other, maintains context across interactions, and offers enhanced contextual understanding compared to ChatGPT's isolated responses.
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Synthetic Users Uptime Monitor
Average Uptime
100%
Average Response Time
239.6 ms
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