Budget for a prediction-market research tool.
A model can help summarize public market information, but fluent output is not proof of a trading advantage. Keep the first version focused on research you can evaluate.
Separate data from interpretation
Collect dated public information through documented APIs. Preserve sources and distinguish market prices from model-generated opinions. Use a read-only system first so analysis cannot place orders by accident.
Make the costs observable
Budget for data collection, model calls, storage, retries, and monitoring. Cache unchanged information and limit update frequency to what the research requires. Compare the API spend with the value of the resulting analysis.
Evaluate without a live wager
Test on historical data and record both correct and incorrect conclusions. Keep model suggestions separate from financial decisions. If you later consider execution, get appropriate legal and risk advice and maintain explicit human control over funds.