The ultimate bidirectional semantic skills and job matching engine.
JANZZsme! is the latest generation of our semantic matching engine for bidirectional skills and job matching. Based on our patented matching techniques, it can also be used for the intelligent application and evaluation of all kinds of occupation (big) data. It can work with both structured and unstructured data, such as:
- Comprehensive labor-market profiles for unemployed individuals and job seekers
- Job offers including job-portal requirements, aggregators or companies’ own job sites
- Profiles from CVs, CV databases or social networks
Via JANZZjobsAPI, the outstanding search and matching functions of JANZZsme! allow for:
- Highly complex queries for extremely precise concept matching (skills and job matching) on a 1 : 1 or 1 : n basis (one-to-one or one-to-many)
- Extensive data mining, for example in the area of occupation data (e.g. ranking of the most frequently requested/offered skills for certain job groups, significant increases in/changes to criteria)
- Considerably improved results in the area of classic full-text searches
- Gap analyses (between job offers, as well as between profiles and job seekers/applicants)
In perfect harmony with JANZZon!, JANZZsme! allows for real, transparent and semantic skills and job matching with a level of precision previously unknown. For an in-depth understanding of semantic matching, please order the white paper on Education Zones – Bridging the Gap Between Candidate Education and Employer Requirements in Online Job Matching.
JANZZsme! follows the OECD Principles on Artificial Intelligence (AI) and can be integrated and used as a cloud solution in existing web environments and applications in a very simple and cost-effective manner via JANZZjobsAPI. It can be used by public employment services, job portals and social networks as well as special applications of personnel services providers, recruitment agencies for temporary employees, ATSs and ERP in the area of HCM and staffing and applications in the areas of statistics, training and labor-market data collection.