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StrataSynth
StrataSynth generates synthetic datasets with structured psychological and social dynamics.
Unlike traditional LLM-generated dialogue datasets, StrataSynth models internal cognitive state before generating language.
Our engine separates cognition from language:
PsycheGraph → identity model
Belief Engine → evolving beliefs
Relationship State → trust, tension, connection
Decision Engine → conversational intent
LLM Rendering → natural language
This produces datasets with explicit belief evolution and relationship trajectories.
Datasets
We publish datasets focused on:
- belief dynamics
- social reasoning
- conversational conflict
- agent stress testing
Current datasets:
stratasynth-belief-dynamicsstratasynth-social-reasoningstratasynth-agent-stress-test
Why structured synthetic data?
Most dialogue datasets only contain text.
StrataSynth datasets include:
- belief_state
- belief_updates
- relationship_state
- intent
- communication_act
- conversation trajectory
This allows research in:
- AI alignment
- social reasoning models
- agent evaluation
- belief tracking
- multi-agent systems
Links
Website
https://stratasynth.com
Platform
https://app.stratasynth.com
Example turn
Speaker A
"I’m not upset about the meeting. I’m upset that you didn’t tell me earlier."
intent: reveal
goal: seek_validation
belief_update: trust_other: -0.07
relationship_state:
trust: 0.62
tension: 0.44