AI agents need consumer understanding at decision time. The Oracle API returns probability-weighted preference distributions in milliseconds — so autonomous systems can make informed choices without waiting for research.
// Agent encounters: "Plan a birthday // party for my 7yo, budget $150" // Oracle returns preference distributions: { "Food & Cake": 0.35, "Entertainment": 0.25, "Decorations": 0.18, "Party Favors": 0.12, "Themed Supplies": 0.10, "latency_ms": 187 }
Autonomous commerce agents — shopping assistants, recommendation engines, personalization systems — make thousands of consumer-facing decisions per second. Each decision requires an understanding of what people actually want. The Oracle provides that understanding on demand.
// Oracle API Request POST /api/oracle/query { "question": "meal planning priorities", "demographics": { "age": "25-34", "income": "$50K-$75K", "location": "suburban" }, "model": "consumer" }
From development-time calibration to live runtime queries.
Pre-compute preference distributions during development. Bake consumer understanding into agent logic as calibrated parameters.
Test proposed agent logic against synthetic populations before release. Measure predicted satisfaction and conversion across segments.
Agents query The Oracle directly when encountering novel scenarios outside pre-calibrated knowledge. Real-time preference data on demand.
Each model is trained on validated domain-specific data and returns calibrated preference distributions.
Shopping behavior, brand preferences, lifestyle decisions, budget allocation. Validated against tier-one consumer panels.
Physician perspectives, prescribing behavior, treatment preferences. 15 medical specialties from primary care to oncology.
Attitudes, values, political opinions, social trends. Demographic and geographic structure validated against major polls.
The Oracle uses fine-tuned language models trained on millions of real survey responses to predict how demographic segments would respond to any question.
// Single Query Request POST /api/oracle/chat { "question": "Which factor matters most when choosing a grocery store?", "options": [ "Price", "Proximity", "Product Quality", "Brand Selection" ], "demographics": { "age": "25-34", "income": "$50K-$75K", "location": "suburban" }, "model": "consumer" }
The Oracle isn't just an API. Researchers and product teams can query it directly through the Simsurveys dashboard.
Ask any research question and get predicted response distributions in seconds. Manual, AI-assisted, or raw input modes.
Run batch queries across multiple demographic segments simultaneously. Compare responses across banners in seconds, not weeks.
Condition predictions on prior response history. "Given they answered X, how would they answer Y?" Layer demographics with conditioning.
Embed validated preference data into any autonomous system. Start querying in minutes.