Campus security
AI-enabled cameras and sensors detecting unauthorised entry, crowding, restricted-area access and potential security incidents.
Product 01 · Vigil.edu
AI on the campus cameras you already own
Bringing AI to existing CCTV infrastructure, for safer campuses and better student insight. The models read the streams your institution already records, so the capability arrives without a rewiring project attached to it.
What it is
A computer-vision platform pointed at a campus
Vigil.edu analyses live and recorded CCTV using deep-learning video analytics, detecting safety incidents, unauthorised access and unusual activity in real time while integrating with the surveillance infrastructure already installed. The same streams also produce the engagement and attendance analytics an academic team can actually use.
- 55parameters and above
- 3module groups
- Nocamera replacement
From a frame to somebody acting on it
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01
Capture
The cameras already covering classrooms, examination halls, corridors, the main entrance and the campus gate, over the cabling and PoE switches already in place.
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02
The recorders you own
Streams reach the engine through the DVR and NVR rack and storage already on site, across the institution's own local network.
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03
The engine
Live stream processing, behaviour analysis, object detection and scene understanding, running on premises or in a local cloud — the institution chooses which.
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04
Dashboard and alert
Events surface on the monitoring dashboard and go out through the alert engine to the people on duty, at their desk and on their phone.
EdTech vision modules
Intelligent detection, operational analytics, predictive monitoring
Those three are how the module set is grouped; the eight capability areas below are how it is sold. An institution enables the ones that match what it is actually trying to solve and leaves the rest switched off.
Classroom safety
Classrooms and campus monitored for unusual incidents, unauthorised access and safety risks.
AI exam proctoring
Suspicious behaviour, unauthorised devices, multiple faces and unusual activity detected during examinations.
Cheating & academic integrity
Suspicious exam patterns, answer-sharing behaviour and other indicators of academic misconduct.
Student engagement monitoring
Attention, participation, attendance and engagement patterns tracked across virtual or physical classes.
Dropout risk detection
Attendance, engagement, grades and learning activity read together to identify students at risk of dropping out. Grades and learning activity are not in a camera stream — this one reads them from your student records system, so it is an integration to scope rather than something the cameras deliver on their own.
Teacher performance insights
Classroom activity, student participation and lesson delivery patterns analysed to support teacher improvement.
Student behaviour analytics
Unusual behavioural patterns identified, with early alerts to administrators or authorised staff.
Say plainly what this watches. Most of these modules do more than detect an event: they infer something about a named person from ordinary behaviour a camera happened to record. Engagement monitoring, dropout risk and student behaviour analytics do it to students; the proctoring and academic-integrity modules do it with disciplinary consequences attached; and teacher performance insights does it to a member of staff, feeding a camera-derived assessment into their professional standing. Deploy them with a written policy, a defined retention period, and disclosure to the students, parents and staff affected. Configure at the level of aggregate patterns rather than individual surveillance wherever the objective allows, and treat a dropout-risk flag as a prompt for a person to look, never as a finding in itself. Local education and data-protection rules get settled before configuration, not after.
Where it watches
The six places a campus already has cameras
- 01Classroom
- 02Examination hall
- 03Reception & main entrance
- 04Hallway & corridor
- 05Campus gate
- 06Security office
Deploy in days, not months
No camera replacement and no operational disruption. The point of reading existing streams is that nothing has to stop while it is installed.
On premise or cloud
On-premise keeps complete data control inside the institution's own infrastructure. Cloud gives secure, scalable, remotely accessible analytics. It is a choice, not an architectural constraint.
Zero infrastructure changes
The platform leverages the existing CCTV ecosystem without major modifications, working with most standard ONVIF-compatible IP camera systems from 2MP upward.
Better cameras, better results
4MP, 5MP, 8MP and higher-resolution cameras deliver enhanced detection precision and AI performance, so an estate can be improved selectively rather than wholesale.
Who it is for
Every educational sector, not just universities
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Bring us the difficult part.
The systems we are proudest of started as the piece nobody else wanted to quote on. Tell us what it is and we will come back with a scope, a fixed price, and an honest answer about whether we are the right people for it.