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Cases

SpeakSoon AI – smart post-submission AI-powered screening & interviewing

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ABOUT THE CLIENT

A higher education institution with a large and diverse international applicant base. The admissions team was looking to streamline the process of evaluating spoken English proficiency, particularly for non-native speakers applying to English-medium programmes.

Business challenge

The university’s admissions team was under growing pressure as international application volumes continued to rise. A key part of the evaluation process—assessing spoken English—relied on manually scheduled interviews, which were time-consuming, inconsistent, and difficult to scale.

To maintain fairness and efficiency while managing increasing demand, the university sought a more standardised and scalable approach to screening language skills—one that could reduce administrative workload without compromising the applicant experience or academic standards.
Key difficulties were identified:
  • High administrative workload: staff were spending extensive time manually scheduling, conducting, and scoring interviews.
  • Inconsistent evaluation: human-led assessments introduced variability and potential bias across interviewers.
  • Scalability issues: the growing volume of applications was not sustainable under the existing resource model.
  • Candidate inconvenience: coordinating live interviews across time zones created logistical challenges and extended the admissions timeline.
As a result, the university was seeking a solution that would streamline assessments, support consistent and objective evaluation, and improve the experience for both applicants and the admissions team.
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Solution
To help tackle the challenges in their admissions process, the university worked with SpeakSoon to implement an AI-powered tool designed to assess spoken English in a fast, fair and scalable way.
Easy integration
SpeakSoon’s system was integrated directly into the university’s existing admissions platform. As part of their application, candidates were asked to complete a short speaking test online, from wherever they were in the world and at a time that suited them.
Bias-free assessments
Instead of taking part in a live interview, applicants recorded their responses to a standard set of questions. These recordings were then analysed by SpeakSoon’s AI, which assessed fluency, grammar, vocabulary and pronunciation. Each applicant received a fair, consistent score — automatically generated and available to admissions staff in real time.
Faster screening with intelligent insights
This meant interviews no longer needed to be scheduled or manually scored, which helped ease pressure on the admissions team. At the same time, admissions staff had access to clear reporting and insights to help them make confident, data-informed decisions.

Key Outcomes

The integration of SpeakSoon’s system brought measurable improvements to the admissions process. By streamlining workflows and introducing AI-driven assessments, the university achieved the following results:

Processing Time
70% reduction in manual workload
The admissions team spent less time organising and evaluating interviews, freeing up resources for other key tasks.
Accuracy Improvement
More consistent and objective assessment
Every applicant was assessed using the same criteria, removing the risk of human bias and delivering fairer outcomes.
Fraud Detection
Easier to scale as applications grow
The university was able to handle increasing application numbers without needing to expand the admissions team.
Fraud Detection
A smoother experience for applicants
Students could take the speaking test at their own convenience, without the stress or delays of arranging live interviews.
Fraud Detection
Better decision-making with data
With clear scoring and performance metrics, admissions teams had everything they needed to evaluate candidates more confidently.
Conclusion
By implementing SpeakSoon’s AI-powered screening tool, the university was able to modernise a key part of its admissions process. The result was a more efficient, scalable and fair approach to evaluating spoken English — saving time for staff and creating a better experience for applicants.
This project shows how digital tools, when thoughtfully applied, can make a meaningful difference in the education sector by solving practical problems and supporting admissions teams to work more effectively.

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