Sandbox decisions, review notes, rejected signals, strategy-card outcomes, AI Coach feedback, and training progress can improve the learning library when consent is granted.
Learning Data
Learning-library growth must be consented, scoped, and reviewable.
CCOR AI can become stronger from customer-approved paper simulation and review data, but sensitive secrets and real account credentials stay outside that loop.
Consent and data policy
Passwords, tokens, provider API keys, broker secrets, payment information, and real account credentials should never enter the learning library.
The confirmation copy should explain that approved learning data can help the learning library grow.
Client-side upload windows should be randomized instead of using one fixed time for every customer, reducing server load spikes.
Customer learning data should enter a review or policy gate before it becomes approved training material.
Customers should be able to decline consent and still use non-learning product areas.
Risk boundary
Research and paper simulation only
CCOR AI is designed for market research, paper simulation, risk review, and decision support. It does not constitute investment advice, does not guarantee returns, and the current Client does not submit live trading orders.