Scholarly is faculty affairs software built for law schools. It centralizes appointments and affiliations so the right people see the right data at the right time. Manage complex rosters in one view, transform CVs into dynamic, AI‑powered profiles, ask plain‑language questions with Scholarly Assistant, and run evaluations and approvals on a secure, compliant platform aligned to ABA reporting. (source, source, source, source, source, source)

• How does Scholarly centralize law school data? * It unifies appointments, affiliations, activities, and outputs in a single system of record—built for complex rosters—with granular, field‑level permissions and comprehensive audit logging to keep sensitive data secure.
• Can Scholarly create AI‑powered profiles from CVs? * Yes. CV Import maps CV content to your template and keeps dossiers current with far less manual entry. (source)
• Which law‑school activity types are supported? * Law review & peer‑reviewed articles; books, casebooks & chapters; case studies & teaching notes; amicus briefs, court filings & opinions; policy reports, white papers & regulatory comments; SSRN/working papers & practitioner pieces; clinics (supervision, outcomes) & pro bono/service; CLE development & executive/legal education; expert testimony, media & public scholarship; invited talks, symposia & workshops; grants/contracts; awards/fellowships; leadership & committee/service roles.
• Can we ask questions in plain language? * Yes. Ask, “Which professors mentored students serving in clinic?” and get permission‑aware tables or charts in seconds—no query building required. (source)
• How are evaluations, reviews, and approvals handled? * Run conflict‑of‑interest, promotion, tenure, leaves, and annual reviews in one platform with real‑time tracking, role‑based permissions, external reviewer support, and one‑click exports. (source, source)
• Is the platform secure and accreditation‑ready? * Yes. Role‑based access, audit logging, encryption in transit/at rest, SOC 2 Type II compliance, and no use of faculty data to train AI models—supporting trustworthy ABA reporting. (source)