DataStorified
Legal & Trust

AI Disclosure

How DataStorified uses AI, communicates uncertainty, and keeps people responsible for final decisions.

Effective: 29 June 2026Updated: 29 June 2026
Table of contents
This document is provided as a platform policy template and should be reviewed by qualified legal counsel before relying on it as legal advice.

1. How AI is used

DataStorified may use AI to structure questions, explain results, summarize trade-offs, suggest next steps, moderate abuse, or assist future creator and API features. Phase 1 decision output is mocked and does not call a paid AI model.

2. AI explanations

AI explanations translate inputs or sourced information into readable language. They may omit exceptions or misstate causation and should be treated as a starting point for verification.

3. AI recommendations

Recommendations reflect available inputs, configured prompts, model behavior, and product rules—not complete knowledge of your goals. They are assistance, not authority.

4. Decision Engine outputs

Decision scores and confidence indicators are decision aids, not probabilities of success or guarantees. The interface should identify mocked, rules-based, and AI-generated elements.

5. Human verification

Users should verify consequential claims with current primary sources and qualified professionals. DataStorified may review feedback but does not pre-approve every generated response.

6. Limitations

Models can generate false facts, broken citations, unsafe suggestions, inconsistent answers, and knowledge that is stale relative to current events or law.

7. Bias and uncertainty

Training data, prompts, evaluation choices, and missing user context can introduce bias. We aim to communicate uncertainty, test high-impact workflows, and provide feedback paths rather than claim neutrality.

8. User responsibility

Do not use AI output to make an automated high-impact decision about another person or as the sole basis for financial, employment, housing, legal, medical, safety, or eligibility action.

9. Data sent to AI providers

Before an external model receives content, the feature should disclose the transfer and relevant provider. Avoid submitting credentials, confidential records, personal identifiers, or regulated data unless the feature explicitly supports them.

10. AI safety

We may apply input restrictions, output filters, rate limits, logging, model evaluation, and human escalation to reduce misuse. Controls are imperfect and do not transfer responsibility away from the user.

11. Feedback and correction

Use in-product feedback when available or email feedback@datastorified.com with the prompt context, problematic output, and expected correction. Do not include unnecessary personal information.

Legal contact

Questions about this document may be sent to legal@datastorified.com.