The AI-native student data layer
edsync centralizes student data from across your systems and adds a semantic layer, so spreadsheets, dashboards, and AI assistants all pull the same trusted numbers, safely and securely.
Student data lives in a dozen systems, and every export, dashboard, and chatbot invents its own definitions. Teams lose hours reconciling numbers instead of acting on them.
Enrollment, attendance, and assessment data sit in separate tools that rarely agree on who a student is.
Each spreadsheet and dashboard re-implements the same metric a little differently, and nobody knows which one is right.
Pointing an AI assistant at raw student records risks wrong answers and exposed personal data.
How it works
edsync connects to your student information, assessment, and attendance systems and resolves in your own data warehouse.
Your team sets metrics, grains, and access rules in the semantic layer. AI helps draft definitions, and people approve them.
Spreadsheets, BI tools, and AI assistants query the layer, not the raw tables, and get the same answer every time.
For school and network leaders
AI assistants can build almost anything on request. The trouble is that ask twice and you may get two different definitions of proficient. edsync makes every artifact follow the business rules your district wrote once, so the same question always gets the same answer.
Safe and secure
Student records are sensitive. edsync enforces access at the layer, so no connected tool can see more than the person using it should.
Permissions follow the person, so a school leader sees their school and a network leader sees the network.
Personal identifiers can be hidden or aggregated before any assistant ever sees a result.
Every query is logged with who asked, which tool asked, and what came back.
Source systems stay the system of record. [YOUR HOSTING AND DATA RETENTION DETAILS]
Integration partners
Join the early access list and help shape edsync for schools and networks.