Is AI screening legal where we operate?

It depends on the jurisdiction and on what the system does. Scoring structured answers with human review is widely accepted; inferring personality or emotion from face and voice is restricted in the EU and in several US jurisdictions. We build the first and refuse the second.

Can candidates ask why they were rejected?

Yes, and they should be able to. Each score links to the competency and the answer it came from, which is what a data-protection request or an employment tribunal will ask for.

Education & EdTech · Recruiting & video interviews

Faculty and staff hiring at scale

Screen high-volume hiring fairly and fast, with the decision left to your people.

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Time to shortlistScreening cost per hireOffer-acceptance and early-attrition rateAdverse-impact ratio by group

The problem

What this fixes

Large intakes of teaching and administrative staff are screened by committees whose time is scarce and whose criteria are applied inconsistently between panels.

Structured asynchronous video and voice interviews with automatic transcription, competency scoring against a published rubric, and shortlisting that a recruiter reviews. Built for volume hiring, retail, contact centres, field crews, graduate intakes, where a shortlist takes weeks today.

Education & EdTech

Structured teaching interviews

The same rubric applied to every candidate, with evidence shown per score.

Education & EdTech

Bilingual candidate pools

Arabic and English answers assessed on identical criteria.

Education & EdTech

Panel time saved for finalists

Committees see a shortlist with evidence instead of a stack of CVs.

Education & EdTech

Documented fairness

Adverse-impact checks and a reason recorded for every decision.

In this sector

Where it earns its place

Delivery

How we build it

Foundation check

Before any build

We inspect the systems, the data behind them and the quality of the records this capability will depend on, then write down what has to be fixed before anything is built.

Narrow first release

First release

One workflow, one team, real traffic, measured against the baseline we captured before we started.

Controls and evaluation

Runs in parallel

Guardrails, approval gates, evaluation sets, logging and the evidence pack your auditor and your regulator will ask for.

Scale and hand over

After sign-off

Additional workflows, sites or languages, then runbooks and training so your team can operate it without us.

Data foundation

What has to be right first

A written competency framework per role family.
Historical hiring outcomes if you want validation, and an honest look at the bias already in them.
An ATS that can accept structured scores and evidence.
Candidate consent and a retention rule for interview recordings.

Controls

Guardrails and KPIs

A human owns every consequential decision

Agents draft, route and execute reversible steps. Anything that moves money, changes a record of consequence or affects a person's rights stops at a named human approver with the reasoning attached.

Every action is logged and replayable

Inputs, retrieved context, model version, output and the human decision are written to an immutable log, so an auditor can reconstruct any single interaction months later.

Data stays where your regulator requires

In-country, in-region or on-premise deployment, with the model portfolio right-sized to the workload instead of routing everything to a frontier endpoint abroad.