AI Campus & Placement Intelligence for institutes

Institutes work from a canonical student roster. Each student record combines verified academics, skills, training, assessments, communication readiness and project evidence — so placement teams see student intelligence rather than a spreadsheet of names.

• Programme, department, batch and section level views of career readiness.
• Skill intelligence showing where cohorts are strong and where they are not.
• Communication readiness across the cohort.
• Student development evidence collected over time, not a single snapshot.

Placement analytics cover drive participation, stage-by-stage progress, offers and outcomes, with the underlying evidence attached. Reporting reflects what actually happened in the platform.

Campuses import or invite their students and link them to the institute record. A student keeps one career profile for life; linking gives the placement cell a governed view of that student's campus-relevant data without duplicating identities.

When an employer opens a hiring drive, Airaw shows which students are eligible and why — the criteria that were met and the ones that were not. Placement teams invite eligible students with those reasons made explicit, instead of broadcasting to everyone.

• Campus-run assessments and mock assessments aligned to target roles.
• Mock recruitment and mock hiring processes that mirror real employer stages.
• Communication checks to prepare students before employer interviews.

See assessments and communication intelligence.

Placement cells manage employer relationships, HR contacts, outreach campaigns and campus drives in one place, with communications, schedules and results attached to the same student and employer records used by the rest of the platform.

Every account sees only what its role permits, enforced in the database rather than only in the interface. Details are on the security page.