Seldon - Finch - Understand different product experiences
Explore how different people experience your product.
Use behavior simulation to catch product and usability issues early. See how your user base interacts with a product change, from prototype to staging, and where there is friction in the user journey.
The question
How do different people experience the same product?
What you examine
UX journeys and product usability
Generic models weren't built to model human behavior.
Plausible isn't the same as probable. General-purpose AI models are good at generating convincing human responses. But a plausible explanation isn't necessarily an accurate representation of how someone would behave. Finch is built on research into human behavior, with technology designed to simulate how people interpret information, make decisions and act.
General-purpose models
Generate a plausible response.
- A model can describe how a hypothetical user might behave without necessarily reproducing the choices that user would actually make.
Finch/Behavioral models
Simulate the decisions behind it
- Model how differences in goals, experiences and available information influence the paths people take and the decisions they make.
From product questions to behavioral insights.
Explore how your users might interact with a new product change, before putting it in front of real people.
Set up your agents
Model your users
Create behavioral agents grounded in real-world clickstream data and enriched with context about your users. Built on Seldon's behavioral technology, designed to capture differences in goals, knowledge, and decision-making.
Bring your product
Choose what to test
Test a prototype, staging environment, or live product. Finch works best with interactive experiences where agents can navigate and explore.
Run your experiment
Run usability tests in silico.
Stress-test assumptions, uncover friction, and explore how different users respond. Get insights early and focus human tests where they'll matter most.
Simulated journeys you can inspect.
Synthetic data extends the reach of real-world data, bringing scale, variation and edge cases. But trust needs to be earned. Simulation works alongside real-world testing, with verification and validation at its core.
Traceability
Follow every journey.
Review the actions and decision points behind a simulated journey. Trace where an agent understood, hesitated or got stuck.
Transparency
Know what informed it.
Inspect the goals, knowledge and context behind each agent's actions, so you can understand why their experiences differ.
Human oversight
Guide the next test.
Use simulated findings to focus your research questions, then test the changes with real people.
Real world
Simulated journeys
Compare where decisions align and where they diverge.
Evidence & evaluation
Calibrate against real behavior
We work with your team to ground behavioral agents in real-world data, from clickstreams to user research and domain-specific context.
By backtesting their decisions against observed human behavior, we can evaluate and refine how accurately they simulate your users.
Stress test your product with behavioral agents.
Bring a problem or a product question that is top of mind and we'll walk through how we can help your team investigate it.
Book a demo