Centralize faculty data, uncover plain-language insights, and streamline evaluations and accreditation- all in one secure, AI-native platform.
Centralize and maintain your faculty data at scale
Accreditation readiness and institutional risk reduction
Incomplete or inconsistent data puts accreditation, trust, and institutional credibility at risk. Scholarly unifies faculty records into a single source of truth, enabling faster, defensible LCME, ACGME, and AAHC reporting with real-time dashboards, permission-aware queries, and auditable evidence.
Promotions and workforce planning
Unclear promotion paths create inequity and limit visibility into faculty growth. Scholarly clarifies every step—tracking appointments and milestones, analyzing time-in-rank by department, and giving leaders real-time insight into progression, planning, and retention.
Managing the faculty experience
Manual entry and duplicative reporting waste time, drain morale, and increase error risk. Scholarly automates faculty data management with AI-powered CV import, external data integrations, and templated workflows, driving higher completion rates, less burnout, and cleaner, more reliable data.
Monitoring clinical productivity and academic output
When clinical, research, and teaching data live in silos, visibility and fairness suffer. Scholarly unifies publications, grants, teaching, and clinical activity into AI-powered dashboards, giving leaders a complete, balanced view of faculty workload, productivity, and ROI.
Data governance, for data confidence
When faculty data lives in spreadsheets, version control breaks down and access risks rise. Scholarly centralizes your data under SOC 2 Type II controls, MFA, and detailed audit logs, creating a single, secure source of truth with role-based access and full accountability.
Institutional insight and strategic alignment
When faculty data is disconnected from strategic goals, opportunities for growth and investment are missed. Scholarly transforms faculty information into actionable intelligence, helping leaders model staffing needs, benchmark performance, and align resources with institutional priorities in real time.







