Find rare expertise. Look beyond the job title.
A title says little about depth of expertise. Talenty supports specialised searches with AI-powered skill matching, passive talent discovery and consideration of technical evidence. For roles where the right combination of experience, domain knowledge and skills makes the difference.
When conventional search terms do not go far enough
A senior blockchain engineer, ML research scientist or SAP FICO consultant can rarely be found by job title alone. Generic keyword matching can miss relationships between skills, technical depth and unusual combinations of expertise. Many suitable specialists are also not actively seeking a new role. Talenty starts with specific requirements and the targeted discovery of relevant expertise.
- Look for skill combinations rather than isolated keywords
- Consider depth, experience and relevant certifications
- Discover passive candidates beyond incoming applications
- Refine requirements with the responsible technical or business team
AI matching for the details that matter
AI helps interpret related skills and relevant experience. A search might require Rust together with WebAssembly and performance optimisation, or SAP S/4HANA combined with finance experience and certification. That brings the professional requirement into focus. Prioritised matches and detailed skill breakdowns give your team a basis for further assessment.
- Define specific skills, certifications and the required depth of expertise
- Include skill relationships and technical specialisation
- Prioritise profiles by relevance to the specific role
- Discuss suitability using a differentiated view of skills
Discover specialists where their work becomes visible
Specialist expertise is not limited to a CV. Talenty's discovery approach also considers professional communities, code repositories, research contributions and specialist platforms. AI assesses skill evidence from code projects, publications and certifications, preparing it for review by your specialist team. The accessible and relevant sources for your search are established around the specific role requirements.
- Consider professional networks and specialist tech communities
- Review code repositories and technical projects as additional evidence
- Include publications and research activity for scientific roles
- Use AI-assisted assessment of skill evidence to support further review
For demanding roles across specialist domains
Search criteria can reflect technical, scientific and industry-specific requirements. Frameworks, research areas and publications may matter for an ML role. Embedded systems hiring may focus on RTOS, ARM, C/C++ and automotive experience. A security architect role could call for Zero Trust, cloud security and relevant certifications. Your hiring team determines the criteria.
- Advanced technology: AI/ML, blockchain, robotics and quantum computing
- Engineering: embedded systems, aerospace and materials science
- Life sciences: bioinformatics, medical devices and clinical research
- Enterprise and security: SAP, Oracle, cloud security and compliance
- Finance and research: quantitative analysis, risk modelling and R&D
From a difficult vacancy to a shortlist you can assess
Start with the skills, experience and evidence that are essential for your role. AI-powered search helps discover relevant candidates and prioritise them by professional fit. Your team then reviews the information and approaches suitable people deliberately. In the demo, explore this process using a hard-to-fill position from your own organisation.
- 1. Agree essential professional criteria and complementary skills
- 2. Set up AI-assisted search across relevant sources
- 3. Review skill evidence and prioritised profiles together
- 4. Reach relevant candidates with professionally informed outreach
Talenty for your everyday recruiting.
Explore AI matching, screening and personalised outreach through your use case.