Signil
Using AI to help hiring teams shortlist faster without sacrificing human oversight.
I handled the design, research and strategy from start to finish.
Year
2025
Services
Product design, research, strategy
Live site
Private
About
Limerick and Clare Education and Training Board (ETB) needed a way to speed up their hiring process without sacrificing quality or human oversight.
We designed and developed Signil, an AI-assisted screening platform that automated candidate application analysis and improved the candidate application experience.
Work started by conducting a workshop with key stakeholders. We focused on the hiring process, pinpointing problems and opportunities for improvement.
Application review was time-consuming.
Applications are long-form, over 1,000 words, resulting in 30+ hours of manual review and several days of shortlisting.
Poor experience caused high dropout rates.
The existing application flow was not built for long-form submissions, causing high dropout rates.
Slow turnaround times lost candidates.
Slow processing times coupled with a lack of visibility of application status often resulted in candidates accepting competitor offers.
Design focused on speeding up application review first. The aim was to give the panel a faster, more consistent starting point while retaining human decision-making.
The user flow followed the existing hiring process, which started by creating the job application form. We built a complex form builder from scratch to meet their unique requirements.
Next, the user would add key requirements that the AI system would use to grade applications. Requirements could be weighted by importance, ensuring more accurate grading.
Applications were reviewed in real time and presented to the user as a list showing their score with supporting reasoning.
Additional details included a summary of their CV, achievements, and grades for each requirement. Every piece of data came with a citation from the original application as evidence.
The application process was designed for long-form inputs. This included clear section navigation, rich text fields, and the ability to save applications as drafts instead of completing them in one sitting.
Applicants could view their submitted application and the status to have better visibility.
By combining an improved application experience with automated, role-specific screening and independent validation, we helped Limerick and Clare ETB reduce administrative overhead while maintaining a strong alignment between AI-generated rankings and the human panel's judgement.
6X
Faster review times
+25 hrs
Staff hours saved per job
75%
Application completion rate
90%
Accuracy vs. human review
<more work>
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