Technical apprenticeship pipelines
L3, L4 and L6 software engineer / data scientist / DevOps standards. IfATE-recognised, BCS-aligned. Designed for the 50–500-cohort apprentice intakes that scaled tech employers run.
18 deployments across UK tech — from FTSE-100 enterprise software to Series-B scale-ups. Technical apprenticeship pipelines, product graduate schemes, data-science cohorts. Skills taxonomy aligned to NCSC, ONS and BCS chartership routes; assessment built around realistic technical work, not coding-trivia tests.
Technology is the sector where the candidates pretend to use AI more obviously than the employers do. Most early-careers tech assessment hasn’t kept up — LeetCode-style problems are now LLM-trivial; take-homes are unscoreable; CVs are sector-aligned but interchangeable.
We assess for the work that won’t change — technical judgement under ambiguity, communication of trade-offs, learning agility on new stacks — rather than skills that AI has flattened.
Tech early-careers hiring is in an awkward transition. The historical filters don’t work. Computer-science degrees are over-represented in the applicant pool but under-correlated with first-year performance. LeetCode-style problems are now solved in seconds by ChatGPT and Claude. Take-home projects are unscoreable when AI does most of the work. CVs are perfectly sector-tuned and tell you almost nothing about how the candidate thinks.
If a coding test can be passed by a 20-line prompt to Claude, it’s a signal-free filter.
What still discriminates is judgement under ambiguity, ability to communicate technical trade-offs, and learning agility on new stacks. None of those show up cleanly on a CV; all of them show up cleanly during a realistic IWX exercise that mirrors the actual work. That’s where we score. The Assessment Platform converts those signals into ranked shortlists; the Video Interview Platform applies AI scoring to the structured technical interview, with explainability per question; the methodology is published so engineering managers can argue with it.
L3, L4 and L6 software engineer / data scientist / DevOps standards. IfATE-recognised, BCS-aligned. Designed for the 50–500-cohort apprentice intakes that scaled tech employers run.
Tuned for product, software engineering, data and platform-team grad pipelines. Includes a non-CS-graduate route — about 30% of high-performers in scaled cohorts come from non-CS backgrounds.
IWX programmes built around debugging, code review, technical writing and stakeholder communication. Scored by behaviour, not output that AI could’ve produced.
Behavioural signals captured during work, not via coding tests. AI-flagging integrated where candidates use AI inside the platform — we don’t penalise it, we measure how well it’s used.
The Video Interview Platform with explainable AI scoring across structured technical questions. Engineering panels stay consistent; junior interviewers get realtime calibration.
First-90-days programmes mapped to BCS Chartered IT Professional progression. Particularly relevant for Civil Service Digital, defence and regulated-industry tech employers.
The platform is configured against the major UK tech-sector skills frameworks. Particularly relevant if you sell into UK government, run security-cleared roles, or care about chartered IT progression.
For procurement: methodology pack, integration architecture and audit reports available under NDA.
Microsoft’s UK technical apprentice scheme grew from 80 to 240 hires per year over three intake cycles on the Talent People platform. Endpoint apprenticeship pass-rate held at 94% through the scaling. First-gen hires rose from 19% to 38% across the same three years. Channel 4’s Immersive Work Experience programme — designed for non-traditional broadcasting-tech backgrounds — delivered an additional 4.4× growth in apprenticeship applications from target schools.
Our tech sector lead is a former engineering manager and a chartered business psychologist. The first conversation usually focuses on what your engineering managers actually want to know about a candidate — and which of those signals AI hasn’t flattened.