Education & EdTech

AI Evaluation & Red Teaming for Education & EdTech

AI Evaluation & Red Teaming for education & edtech, built around the constraint that defines the sector: student data protection and academic integrity constrain what may be automated at all.

Regulations in scope
4
Systems we integrate
4
Typical first release
6 weeks

What changes when it is education & edtech

Orqent Labs red-teams AI systems before launch and leaves behind the evaluation harness your team runs on every change.

In education & edtech, student data protection and academic integrity constrain what may be automated at all. That single fact reshapes how ai evaluation & red teaming has to be built here, the guardrails, the approval points and the evidence trail are design inputs rather than things bolted on before go-live.

The workload we are most often asked to take on first is administrative query handling, usually integrated against LMS. We build the smallest thing that proves the case, put it in front of real users, and expand only what earns its keep.

Multi-model by default, so a provider outage is a routing decision rather than an incident. Six weeks to something running in production, not six quarters to a strategy document.

The sector constraints we design around

Defining constraint
student data protection and academic integrity constrain what may be automated at all
Regulations in scope
DPDP Act 2023 · UGC and AICTE norms · examination integrity rules · child data protection
Systems of record
LMS · student information systems · assessment platforms · ERP
Where we usually start
administrative query handling

AI Evaluation & Red Teaming workloads in education & edtech

  • administrative query handling
  • assessment feedback drafting
  • content adaptation by level
  • attendance and records automation
  • admissions document processing

What is included

  • Evaluation set built from your real domain
  • Adversarial prompts including injection and jailbreak attempts
  • Hallucination rate measured, not estimated
  • Bias testing where the use case warrants it
  • Regression suite wired into your CI
  • Findings report with severity and remediation

Questions from this sector

Will this help students cheat?

Design decides that. We build assistance that shows working and prompts reasoning rather than producing submittable answers, and we set that boundary with your academic leadership.

Is student data protected?

Yes, minimisation, retention limits and access control, with particular care where minors are involved.

What is prompt injection?

An attack where instructions hidden in content the model reads, an email, a web page, an uploaded file, override your intended behaviour. It matters the moment your system processes anything a user or third party supplies.

How do you measure hallucination?

Against a labelled question set from your domain with verified answers, reported as a rate rather than an impression.

Do we need this if we use a major provider?

Yes. Provider safety training covers general misuse; it knows nothing about your specific tools, data and permissions, which is where the real risk sits.

AI Evaluation & Red Teaming for education & edtech, worth a conversation?

Tell us the workload and the regulation it sits under. We will tell you what is realistic.

Or email bd@dtrasglobal.com · call +91 74118 77878