Every respondent starts with a real voice.
Real data, shaped into a usable panel.
Market Pilot follows the question to the right sources, builds a respondent panel for that run, and keeps the evidence trail attached.
Turn public conversations from major platforms into evidence-rich respondent profiles.
Use interview material when motivation, language, and nuance matter more than volume.
Bring first-party data to build a reusable respondent base for your own category.
One respondent base, two operating loops.
The offline loop turns source material into a respondent pool. The realtime loop reuses that pool for each research question, with deterministic checks before LLM judgment.
Data side
Public voices, author context, and comment evidence
Deterministic local rules, reversible and auditable
LLM inference only when evidence exists
Remove empty profiles and assemble the respondent base
Each agent keeps source evidence, confidence, and NA boundaries.
Run side
Check whether the question can be answered
Check whether the sample is strong enough
Tie each answer to profile evidence
Mask sensitive details before delivery
A respondent is extracted, not invented.
Raw social data needs discipline before it can become research. We pass it through layered governance before any answer is generated.
Remove placeholders, empty reactions, and symbol-only replies, while keeping an auditable trail of what was filtered.
Every profile field is stored as a value, confidence level, and source evidence. Unsupported fields stay NA.
Zero-signal profiles are excluded. Every retained respondent is anchored in actual language and context.
Why the system can stay honest.
Other tools always answer. Market Pilot can say, “not enough evidence.”
A scope gate checks whether the question is answerable; a capability gate checks whether there is enough evidence.
Missing evidence is marked as NA. A thinner answer is better than a confident hallucination.
Agents infer attitudes only from profile context, and every answer must stay tied to evidence.
Traceable inside the system, privacy-safe in the product. Phone numbers, handles, and sensitive details are masked with intent.
Click from a report sentence back to the evidence.
Traceability is built into the workflow: final claims, respondent attitudes, evidence lines, and masking rules have to line up.
Price-drop anxiety is the heaviest negative signal in this sample.
This sentence is not written from intuition. It must trace back from the final report, to aggregated attitudes, to respondent evidence.
I picked up the car three months ago and it dropped by over 20k. I should have waited. Calling 138****6021 did not help.
Infer attitude toward price cuts from directly stated frustration.
Do not invent income, household status, or budget. Unsupported fields remain NA.