Codility is a technical assessment platform built on documented assessment science. It helps engineering and talent teams evaluate technical skills for hiring and map verified capabilities across existing workforces. Every assessment is designed by occupational psychologists, validated against an Engineering Skills Model drawn from 30+ international frameworks, and monitored for adverse impact at every measured cut score.
AI has changed how engineering teams deliver. Organizations need signal on who can build in this environment, backed by methodology that holds up when questioned. Codility provides that signal across three workflows: screening candidates with validated technical assessments, running structured live technical interviews, and verifying skills across internal engineering teams.
For screening, Codility provides a task library of 1,200+ validated assessments covering real-world work simulations, algorithmic challenges, SQL, and project-based tasks across 80+ languages and frameworks including Python, Java, JavaScript, TypeScript, C#, Go, Rust, Kotlin, React, Angular, Vue.js, Spring Boot, Django, Terraform, Kubernetes, and TensorFlow. Scoring is automated on supported task types with detailed candidate comparison, configurable time limits, and role-specific weighting. Assessments are reviewed by occupational psychologists and follow documented methodology with auditable scoring.
For live technical interviews, the platform provides a shared VS Code environment with terminal access, sidecar services for databases, caching, and message queues, a collaborative whiteboard, and full session transcript and recording. Engineering teams evaluate candidates in a real development environment. Talent teams get a repeatable process with rubric scores and session playback after every interview.
Organizations control how AI is handled in every assessment. Teams set their AI posture role by role: provide candidates with a monitored AI assistant and review how they prompt, evaluate, and debug with AI, or restrict AI access to evaluate core technical skills independently. Both approaches use the same set of controls and produce a reviewable record of all AI activity. One platform supports AI collaboration assessment and unassisted evaluation with full auditability.
Integrity controls are layered to support defensible hiring decisions. These include identity verification, behavioral signals, risk scoring, similarity detection, paste volume measurement, and automated follow-up questions designed to verify understanding. Follow-up questions are deliberately not scored, to avoid introducing bias. When AI is enabled, reviewable AI activity helps teams distinguish between a candidate's own work and AI-assisted output. All signals produce a defensible record for human review.
Skills Intelligence provides verified technical skills visibility for existing engineering teams. Organizations use it to identify capability gaps, benchmark skills across teams, and support workforce planning with assessed data rather than self-reporting. Hiring assessment and internal skills verification share the same validated methodology, giving organizations one assessment science foundation across the full talent lifecycle.
Codility is SOC 2 audited, ISO 27001 certified, GDPR and CCPA compliant, WCAG 2.1 AA accessible, and aligned with EU AI Act requirements for high-risk AI classification. Assessments follow documented methodology structured to APA Standards, with a 76-page Technical Manual, adverse impact data at every cut score, and an explicit posture: no AI or ML is used in automated hiring decisions. Data is hosted in either EU or US regions. The platform integrates with 20+ applicant tracking and scheduling systems (ATS) including Greenhouse, Workday, SAP SuccessFactors, iCIMS, SmartRecruiters, Lever, Eightfold, and Ashby, with 80+ HRIS integrations for Skills Intelligence. It supports SSO via SAML 2.0 and offers API access for custom workflows.
Founded in 2009, Codility is used by engineering and talent teams at Barclays, BMW, Deutsche Bank, GitHub, Samsung, SpaceX, and other organizations evaluating technical skills across both AI-assisted and traditional engineering workflows.
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Lindsey Ludwick (Denver GMT-7)