Unibeez

Aduro partnered with Unibeez to design and build a graduate recruitment platform for the UK — connecting students and recent graduates with employers who want to hire upcoming talent. Trusted by over 500 brands and covering universities and colleges nationwide, Unibeez needed a platform rebuild that could scale on both sides of the marketplace. Aduro led the data, AI and security architecture — making executive decisions on how profiles, matching, hiring workflows and access control should work before development began.

A marketplace for graduate talent

Unibeez sits between two audiences with fundamentally different needs. Students arrive with limited work history but growing potential — they need to register a CV, discover relevant roles, save opportunities and apply with confidence. Employers need to post vacancies quickly, review applicants, search talent proactively and move candidates through a hiring pipeline without losing momentum.

The strategic question was how to serve both journeys on one platform without compromise. We shaped the architecture around distinct student and hirer experiences — shared identity and messaging, but separate workflows, permissions and data models — so each side could move quickly without passing complexity on to the other.

Job discovery built for students

The student experience opens with a clear path: build a CV, find jobs, get hired. Search spans job titles, skills and companies with location filtering across UK cities and postcodes. Students can browse trending roles, explore all vacancies and save jobs to return to later — with registration unlocking richer filtering as they commit to the platform.

Behind the interface, our architectural decisions focused on how job data should be indexed and surfaced — fast filtered search for active browsing, and semantic discovery for roles that match a student's profile even when the wording does not align. That dual approach lets students move quickly through listings while still benefiting from intelligent recommendations as their CV develops.

Hiring at speed for employers

On the employer side, Unibeez leads with a direct value proposition: hire students fast. Hirers create an account, post vacancies and match talent from a pool of upcoming graduates — with major brands already on the platform providing social proof for new recruiters joining the marketplace.

We designed company and team structures into the data model from the outset — account owners, administrators and members with different permissions — so hiring activity could scale across an organisation without every user seeing the same jobs or the same applicant data. That was an executive decision about how company hierarchy should map to platform access, not just a permissions checklist.

AI that understands candidates and roles

Keyword search fails graduates whose experience does not map neatly to job titles. Unibeez needed matching based on what candidates can actually do. Aduro designed a semantic matching pipeline: uploaded CVs are interpreted into structured profiles — bio, skills, education, work history and interests — and job descriptions are understood in the same way, so candidates and roles can be ranked by fit rather than text overlap alone.

For employers, that means AI-suggested talent surfaced with confidence thresholds — strong matches without flooding recruiters with noise. Hirers can also paste or describe a role and have AI prefill a job post in seconds. For students, uploaded CVs become searchable profiles without manual data entry. These were executive decisions about when AI should suggest, when it should stay in the background, and how to keep humans in control of hiring decisions.

Managing the full hiring pipeline

Once jobs are live, hirers need operational visibility — not just a list of postings. The employer dashboard brings active, draft and inactive jobs together with applicant counts, new application alerts and controls to manage listing visibility. Recruiters can toggle between their own jobs and company-wide listings, sort by recency, and move directly into applicant review from the job card.

In-app messaging connects the pipeline end to end, so conversations stay tied to applications rather than scattering across email. Daily digests and notification flows keep recruiters responsive without requiring them to live inside the platform — another architectural choice about how hiring activity should propagate through the system.

Architecture for scale and trust

A platform handling CVs, company data and hiring conversations needs more than a polished interface. We built Unibeez on serverless AWS infrastructure with separate staging and production environments, role-based access for students, hirers and company teams, and protected file delivery for sensitive documents.

Background processing keeps search indexes and match suggestions current as profiles change — without blocking the experience users see. The result is a platform that can absorb growth across hundreds of employer brands and UK-wide university coverage, while keeping personal data and hiring activity appropriately protected.

From student onboarding and CV creation through to employer dashboards, AI-powered talent search, applicant tracking and in-app messaging, Unibeez is a full hiring marketplace — with AI and security woven through the architecture, not bolted on afterwards.