Map skills to internal opportunities. White-label under your domain.

Two integration patterns. (1) Lightweight — JobCannon outputs Career Match recommendations using its 2,536-career taxonomy; your talent-marketplace platform (Gloat, Eightfold, Fuel50, SAP SuccessFactors Opportunity Marketplace) consumes the assessment baseline as one input alongside its own internal job-posting taxonomy. (2) Deep — for partnership-tier deployments we map our knowledge graph to your internal job-architecture taxonomy so Career Match output speaks directly to your internal openings. The platform is not a talent marketplace itself; it is the assessment-and-discovery layer underneath whichever marketplace platform you run.

Real risk that needs addressing in deployment. Three patterns work. (1) Open enrolment framing — "this is available for any employee curious about internal pivot, used at your discretion" rather than assigned task. (2) Manager opt-in — managers do not see employee assessment data unless the employee chooses to share. (3) Anonymous dashboard — L&D sees aggregate department-level archetype distribution but not individual-level data unless employee shares. Companies deploying with these three properties report assessment completion rates of 40-60 percent of eligible employees in the first quarter; companies deploying with assigned-task framing and manager visibility report 5-15 percent and significant cynicism.

Indirectly. Assessment data feeds an employee's self-development plan and the development conversation with their manager. The platform does not produce talent-review ratings or succession-planning placements — those are management decisions made with HR, not algorithm decisions. Some companies use aggregate Career Match patterns to identify under-represented internal-mobility pathways (e.g., engineering-to-product-management is theoretically strong but actually rare in our company; what is blocking it?). The aggregate signal informs L&D programme design without driving individual placements.

GDPR and CCPA require explicit, granular consent for psychometric assessment use in employment context. The platform deploys with default participant-controlled consent (employee sees what is collected, why, and can request deletion at any time). Enterprise clients in EU operations sign a Data Processing Agreement aligned to Article 28 GDPR. California employees get CCPA-aligned notice. The platform does not transfer data to third countries without standard contractual clauses. We do not perform any automated decision-making affecting employees under Article 22 GDPR; the platform is a self-discovery tool, not a hiring or promotion algorithm.

Different layer. LinkedIn Learning and Coursera for Business deliver content; JobCannon delivers career-discovery and pathway data. The platforms work together: an employee takes the JobCannon assessment, identifies a career pivot, and the development plan recommends specific LinkedIn Learning paths or Coursera specialisations to close the skill gap. We do not deliver training content; we identify which content matters for the pivot the employee is considering.

The platform does not gate Career Match outputs by internal-only roles. An employee whose Career Match suggests their best fit is outside the company will see that. Companies that try to suppress external matches damage trust and increase regretted attrition. The empirical pattern from companies running the platform openly is that employees who learn their fit is external pivot 6-12 months later in a managed transition rather than 6-12 weeks later in a panic exit, which actually reduces total attrition cost.