Most recruitment compliance software checks a candidate once and trusts the result until someone remembers to renew it. That gap — between when a check happened and when a shift actually starts — is where placements go wrong. Here’s exactly how we close it.
A right to work check, a DBS certificate, a professional registration — every one of these has a shelf life. Some expire on a fixed date. Others lapse quietly: a visa condition changes, a registration is suspended, a DBS certificate’s update service flags something new. Industry-standard practice is to check at onboarding and set a renewal reminder. That’s better than nothing. It is not the same as knowing a candidate is compliant on the actual day they turn up to work.
Every AI recruitment platform we researched frames “compliance” as a governance question about its own systems — SOC 2 certifications, GDPR statements, responsible-AI charters. Those matter, but they describe how the platform handles data, not whether the person it’s placing is actually cleared to be there today. We built the dual-checkpoint model specifically to close that second, more consequential gap.
Every candidate sourced from a client’s own consented CRM is verified individually — right to work, DBS or equivalent background check, professional registration where relevant, training currency, and references. Each item is checked separately against its own authoritative source; nothing is inferred from a single composite “pass” score. This is the checkpoint every serious platform in the category performs. We treat it as the floor, not the finish line.
Immediately before a placement is confirmed as starting, every checkpoint-one item is re-verified live against its current authoritative source. If a registration lapsed last week, if a right-to-work condition changed, if a DBS update-service flag appeared since screening — the placement does not proceed until it’s resolved. This is a structural hard stop in the pipeline, not a warning a human can override under time pressure. See where this sits in the full eight-stage pipeline
Recruitment compliance is not one undifferentiated pass. Candidate identity, right-to-work evidence, professional registration, background checks, training and client-specific requirements each have their own source, status and review point. The SOS approach keeps those items visible separately so an exception cannot disappear inside a composite score.
Automation can collect, structure and surface evidence, but the agreed authoritative source and responsible human remain decisive. Where a status changes or cannot be verified, the workflow routes the issue for review before progression or placement.
UK GDPR’s treatment of automated decision-making turns on whether human involvement is genuine — someone with real authority to change the outcome, reviewing the actual case, not rubber-stamping a system’s output after the fact. Our placement-day checkpoint is designed around that standard directly: a flagged discrepancy routes to a named human with the authority to resolve or halt it, every time, regardless of deadline pressure. We’d rather lose a placement to a compliance gap than paper over one.
Fewer compliance write-offs. No placement goes live on a technicality nobody caught. And when a client, auditor, or framework body asks “how do you know this candidate was actually compliant on day one” — the honest answer is a re-verified, timestamped record, not a screening file from six weeks earlier.
No legal or regulatory claim on this website should be treated as legal advice. Current official sources, the precise operating model and appropriate qualified review are required before publication or technical activation.
Which sources we check against, how the placement-day re-verification integrates with your existing CRM, and where the human review point sits in your specific workflow.
Compare evidence-led recruitment automation with conventional feature-led platforms.
See the workflow for healthcare staffing, locum recruitment and placement-day checks.
Review right-to-work, DBS and professional-registration evidence requirements.
Use the source-led UK framework to define legal, sector, client and recommended controls.
Open the UK recruitment compliance checklist ↗Follow synthetic candidate evidence through an exception, human review and placement sign-off.
Run the recruitment workflow demonstration ↗Apply the control model to your roles, systems, approved sources and decision owners.
Book a tailored demonstration ↗Configure evidence-led automation, bounded agentic workflows, exceptions and human authority around a defined business process.
Explore AI systems and business automation ↗Connect application, interview, verification and onboarding identity with proportionate fraud controls and review.
Use the candidate identity checklist ↗Apply identity, permissions, monitoring, intervention, revocation and audit to AI agents.
Use the governance framework ↗