Embed validated career assessments in your product.

It exposes the JobCannon assessment engine as a programmable layer for your product. Three primary use cases. (1) Embed assessment delivery — your users take RIASEC, Big Five, or Skills Audit inside your app and you get scored results back. (2) Submit prior assessment data — push existing personality or skills data into the engine and get back a JobCannon-format Career Guide with 2,536-career matches. (3) Subscribe to webhook events — every assessment completion, every Career Guide generation, every consent change fires an event you can react to in your existing case-management or LMS system. The API is a RESTful JSON interface with OAuth 2.0 client-credentials authentication, sandbox and production environments, idempotent endpoints, and predictable rate-limiting.

Five common adopters. (1) HR-tech vendors embedding career-assessment as a feature inside an applicant tracking system or LMS. (2) Workforce-board case-management systems integrating assessment data into participant records for WIOA reporting. (3) University career-services platforms surfacing JobCannon Career Guide inside the student portal. (4) Coaching SaaS products giving coaches access to validated psychometrics inside their existing client tooling. (5) Internal corporate L&D platforms embedding assessment as part of an internal mobility programme. Each integration runs about 1-3 engineer-weeks for a typical implementation; we provide reference implementations and a sandbox.

POST /assessments — start an assessment session for a user, returns a session token. GET /assessments/{id}/questions — retrieve question payload (paginated). POST /assessments/{id}/answers — submit answers (idempotent). POST /assessments/{id}/complete — finalise scoring and generate result. GET /career-track/{user_id} — retrieve a user’s current Career Guide with skill-gap analysis and course recommendations. GET /careers/{slug} — query the 2,536-career database. POST /webhooks — register webhook URLs for completion events. Documentation includes OpenAPI spec and Postman collection.

Default rate limit is 1,000 requests per minute per API key on Business tier; partnership engagements get higher limits scoped to expected volume. Burst capacity allows 10x the steady-state limit for 30 seconds — handles cohort-completion spikes (50 students hit submit at the end of class). Rate-limit headers (`X-RateLimit-Remaining`, `X-RateLimit-Reset`) appear on every response. Exceeded limits return 429 with `Retry-After`. We do not throttle silently or drop requests.

Three primary resources. (1) Users — represent your end users (you provide an external ID; we mint our internal user). (2) Assessments — represent a session of a single instrument (e.g. one RIASEC run). (3) Career Guides — represent the AI-generated career-match output, refreshable on demand. Plus secondary resources for careers, skills, and webhook subscriptions. The API is resource-oriented and predictable; you can build a working integration from the OpenAPI spec without reading every endpoint individually.

Most teams that consider building career-assessment in-house underestimate three costs. (1) Psychometric instrument validation — RIASEC, Big Five, EQ are public frameworks but validated item banks and scoring algorithms are not; building your own validates over years and tens of thousands of administrations. (2) Career data — mapping psychometric output to careers requires a knowledge graph (we have 2,536 careers, 1,533 skills, 64,317 edges); building this from O*NET takes 6-12 engineer-months. (3) Maintenance — instruments drift, career data changes, item banks need refresh. Most teams that start in-house abandon at the 18-month mark and license. The API is the shortcut.