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Enabling Operational Capability Intelligence

Enabling Operational Capability Intelligence

Headai recently participated in Finanssiala’s Ajatustori event, which brought together experts and thought leaders to discuss the changing skills needs in the financial sector. The conversation emphasized the growing demand for future-oriented competence development and the importance of understanding skills from a data perspective. As industries evolve, so must the ways we track, anticipate, and support workforce capabilities.

During the event, Headai contributed to the dialogue by showcasing how our cognitive AI technologies — such as knowledge graphs and self-organizing maps — can be used to identify skill gaps and inform strategic planning. By enabling a common language for skills and competencies, our approach helps align education, employment, and policy decisions with real-time labour market needs. The full article, published by Finanssiala, is available in Finnish:
Ajatustorilla keskusteltiin finanssialan osaamistarpeista

Build curricula for what comes next

Build curricula for what comes next

Use skills data to understand changing labour-market needs and keep education aligned with the skills that matter.

Use skills data to understand changing labour-market needs and keep education aligned with the skills that matter.

Understand local skills demand

Understand local skills demand

Identify emerging skills gaps

Identify emerging skills gaps

Compare education with labour-market needs

Compare education with labour-market needs

Track how skills needs change over time

Track how skills needs change over time

Helping YTK members find work that matches their real skills

Job seekers couldn’t see which of their skills mattered, or which jobs actually fit. Headai built a skills-based recommendation engine, now live in production with 1,500+ monthly users and growing.

Job seekers couldn’t see which of their skills mattered, or which jobs actually fit. Headai built a skills-based recommendation engine, now live in production with 1,500+ monthly users and growing.

Turning fragmented skills data into shared decisions with LEADSx2030

Europe’s skills demand, education provision and technology signals were fragmented. LEADSx2030 now connects the evidence in one public Observatory, helping users compare demand and supply and identify where to act.

Europe’s skills demand, education provision and technology signals were fragmented. LEADSx2030 now connects the evidence in one public Observatory, helping users compare demand and supply and identify where to act.

Seeing what's actually happening in an industry, before it shows up in official statistics

Official statistics show what already happened. Headai's Growth Agents track 20 technology areas in real time, using one unified data language so frontier AI can analyze industry signals without hallucinating, and trace every insight back to its source.

Official statistics show what already happened. Headai's Growth Agents track 20 technology areas in real time, using one unified data language so frontier AI can analyze industry signals without hallucinating, and trace every insight back to its source.

Turning clinical notes into explainable ICF and ICD codes

Most patient record data is free text, hard to compare or analyse at scale. Headai's Health Coder turns clinical notes into ICF and ICD codes, each traced to the passage it came from. Validated in two peer-reviewed studies in 2025.

Most patient record data is free text, hard to compare or analyse at scale. Headai's Health Coder turns clinical notes into ICF and ICD codes, each traced to the passage it came from. Validated in two peer-reviewed studies in 2025.

Consistent where generative AI is not: keywording 5,585 project applications

Rural development applications were keyworded by hand, unevenly. Headai structured 5,585 applications against an 84-term ontology, raising the average from 3.9 to 4.9 keywords per application and suggesting useful new themes for 99.5% of them.

Rural development applications were keyworded by hand, unevenly. Headai structured 5,585 applications against an 84-term ontology, raising the average from 3.9 to 4.9 keywords per application and suggesting useful new themes for 99.5% of them.

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into intelligence?

Ask questions across your organisation’s information without query languages or specialist tools.

Ready to turn information

into intelligence?

Ask questions across your organisation’s information without query languages or specialist tools.