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AI output, privacy and human review

AI Services Disclaimer

This Disclaimer explains the limits of AI-assisted features used in Elqorin Pocket projects and why AI output, privacy architecture, provider behavior, and human review must be evaluated for each workflow.

Last updated: September 24, 2026 Elqorin Pocket Colorado · formed September 21, 2026

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1. AI is assistive technology2. Accuracy limitations3. Human review4. High-impact decisions5. Private AI meaning6. Model training and retention7. Input responsibility8. Provider changes9. Testing and controls10. No professional advice

1. AI is assistive technology

AI functionality is designed to assist users with workflow tasks such as transcription, extraction, summarization, classification, image or document interpretation, structured output, and draft generation. It should not be treated as inherently correct simply because a result is produced confidently.

2. Accuracy limitations

AI systems may return inaccurate, incomplete, outdated, ambiguous, or fabricated information. Voice recordings may be transcribed incorrectly, images may be misinterpreted, documents may be parsed incorrectly, and structured outputs may omit or misclassify fields.

3. Human review

Where an AI result can materially affect business actions, records, customers, employees, property, safety, finances, or legal rights, the result should be reviewed by an appropriately authorized person before action is taken.

4. High-impact decisions

Unless a use case is specifically designed, validated, and contractually approved for a regulated environment, AI features should not be used as the sole basis for employment, credit, health, insurance, eligibility, legal, safety, or other high-impact determinations.

5. Private AI meaning

“Private AI” does not automatically mean that all processing occurs locally or that no provider ever receives data. The intended architecture may combine on-device models with controlled cloud AI services. Project documentation should state the actual processing location, providers, access controls, retention, deletion, and training settings.

6. Model training and retention

Provider policies differ by product and service tier. Elqorin Pocket does not promise universal zero-retention or no-training behavior unless the selected provider, configuration, and contract actually support those conditions.

7. Input responsibility

Clients must ensure they have authority to submit information to the AI workflow and should avoid placing regulated or highly sensitive data into AI services unless the project explicitly permits and protects that use.

8. Provider changes

AI providers may update models, policies, pricing, rate limits, safety systems, or availability. These changes can affect output behavior, performance, and integration requirements. Maintenance plans may include adaptation to such changes.

9. Testing and controls

Depending on the workflow, projects may use validation rules, structured schemas, permissions, confidence checks, logging, human review, restricted prompts, or escalation paths. These controls reduce risk but do not eliminate the possibility of incorrect output.

10. No professional advice

AI output does not itself constitute legal, medical, tax, financial, accounting, engineering, or other regulated professional advice. A qualified professional should independently review matters that require licensed judgment.

Company contact information

EMAIL: projects@elqorinpocket.com

ADDRESS: 7950 W Colfax Ave, Lakewood, CO 80214

PHONE: +1 860 846 7486

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Elqorin Pocket

Mobile application development and private AI workflow engineering for businesses. Focused on practical iOS, Android, cross-platform, automation, integration, and ongoing product support.

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