Scholify uses AI to collect, structure, compare, and update scholarship and application information at scale. AI does the heavy lifting, while quality systems monitor for stale data, missing sources, contradictions, and possible AI errors.
We do not treat AI output as final authority. Low-confidence or high-impact records are labeled clearly, reviewed, corrected, and improved over time.
Scholify provides decision support, not final legal, admission, financial, visa, or scholarship authority. Students should always review the linked official source before submitting an application.
Scholarship and university data should include source links, attribution, and provider context wherever available.
Deadlines, award amounts, eligibility rules, and unusual source changes are monitored for staleness and review risk.
AI-imported and scraped records carry confidence signals so students can distinguish strong data from developing coverage.
Low-confidence, high-impact, or contradictory records are routed for admin review and correction.
AI helps collect, normalize, compare, and update scholarship information at scale.
Backend checks monitor hallucination risk, missing citations, stale data, duplicate records, and suspicious changes.
Corrections from admins, outcomes, and source updates are fed back into the product and recommendation quality.
Students are shown source quality, confidence, and last-verified context where it affects a decision.
We aim for best-effort accuracy using source-backed data, confidence scoring, freshness monitoring, automated anomaly checks, and manual review for risky records.
We do not guarantee admission, award selection, funding availability, visa outcomes, deadline correctness, or provider decisions. Final eligibility and selection always remain with the university or scholarship provider.
Source-backed guidance with transparent confidence signals. If certainty is limited, the product should say so clearly.