Edhivo: An AI-Native Platform for Scalable Assessment and Instant Feedback in Higher Education

Edhivo is an AI-native pedagogical platform developed to address higher education assessment bottlenecks, specifically the faculty burden of test authoring and the operational difficulty of semantically evaluating open-ended responses. Utilizing a vertically integrated infrastructure and a Dual-LLM pipeline, the platform generates context-aware assessments from instructor materials and conducts multi-criteria, rubric-based student evaluations to facilitate rapid feedback cycles.

This development marks an operational shift toward specialized, multi-model AI pipelines designed to solve domain-specific workflow bottlenecks rather than relying on generalized conversational interfaces. For higher education and training organizations, automating both curriculum assessment generation and subjective evaluation directly addresses instructional capacity limitations. It enables scalable, continuous feedback loops without requiring a linear expansion of faculty or grading resources.

Higher education assessment faces dual operational constraints: high cognitive effort in authoring assessments and limited capacity to semantically grade open-ended student work.

Forward consideration, not a verified fact.