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Writing recommendations is one of the most time-intensive tasks for counselors and teachers. The Recommender Agent creates a well-structured first draft using student profile data and brag sheets—then staff can refine and personalize before submitting.
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For districts managing high volumes of work-based learning placements, the Form Completion Agent bulk-fills free-response fields using information already stored in SchooLinks—then presents a preview table for staff review before saving.
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The Alert capability is designed to flag important student actions and behaviors across the platform—so counselors and directors don’t have to discover problems at the end of the semester.
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Predictive nudges recommend practical next steps (follow up, schedule, remind, or guide) based on real student activity—so staff can take action faster, with less guesswork.
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As part of the Agentic AI roadmap, “Analyze” focuses on making district data easier to interpret—so teams can quickly understand who needs help and why, without manual slicing and exporting.
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SchooLinks designed its AI workflows to minimize data exposure, keep actions auditable, and operate within the same role-based access controls districts already rely on.
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SchooLinks AI features are designed to operate in compliance with FERPA, using role-based access controls and purpose-limited educational use.
No—PII is not used or is masked, and it is not used to train models outside SchooLinks’ infrastructure.
No—staff generate a draft, then review/edit before submitting. It’s designed for educator oversight.
It generates responses using existing data in SchooLinks related to the candidate, sponsor, and program, then shows a review table before saving.
The agentic approach is designed to be integrated into workflows and not require staff training in AI/prompting skills.
SchooLinks emphasizes context + workflow integration—AI outputs are embedded where staff can review, approve, and act.
