France-Based Cybersecurity Recruitment Agency

The Business Challenge

The client is a France-based recruitment agency specializing in sourcing highly skilled cybersecurity engineers for organizations in sectors including technology, finance, and government.

Cybersecurity recruitment is highly time-sensitive. When a client submits a new requirement, multiple agencies may be competing to deliver qualified candidates first. The client's existing process depended heavily on manual candidate filtering, profile anonymization, and document preparation.

Candidate information was collected from multiple sources and had to be reviewed manually against requirements such as technical skills, certifications, years of experience, and cybersecurity specialization.

Depending on the request, candidate matching and filtration could take between 3 and 5 days.

The agency also needed to protect candidate confidentiality. Before profiles could be shared with clients, personally identifiable information had to be removed while preserving relevant skills, experience, certifications, and professional background.

Once candidates were shortlisted, recruiters manually prepared standardized application forms for client submission. Each form could take approximately 30–40 minutes per candidate.

For urgent opportunities where clients expected qualified candidates within hours, these manual steps created a direct commercial disadvantage.

What Cogya Built

- Cogya designed a custom AI recruitment system around the agency's actual candidate sourcing and submission process.

- The system connected candidate data, qualification criteria, AI-assisted matching, anonymization, and client-ready profile generation in one structured process.

- Cogya first centralized candidate information into a structured environment, giving recruiters one place to access and evaluate profiles rather than manually gathering information from multiple sources.

- The system then used AI-assisted matching and filtering to evaluate candidates against role requirements such as technical skills, cybersecurity certifications, years of experience, specialist knowledge, and other client-defined criteria.

- Candidates could be prioritized according to their alignment with the requirements, allowing recruiters to focus on the strongest potential matches rather than manually reviewing every profile.

- Cogya also automated the anonymization process, removing selected personally identifiable information while preserving the professional information required for client evaluation.

- Finally, the system automated the generation of standardized client-ready application forms. Once a candidate was selected, the system could transform structured candidate information into a consistent anonymized profile within seconds.

- Recruiters remained responsible for reviewing candidates and making the final decision on which profiles should be submitted to the client.

How the System Works

The recruitment process was redesigned around six connected steps:

- Collect — Candidate information is centralized and structured. - Match — The AI engine compares candidate qualifications with the client's recruitment requirements. - Rank — Relevant candidates are prioritized based on skills, experience, certifications, and selected criteria. - Anonymize — Personally identifiable information is removed from client-facing profiles. - Generate — Standardized candidate application forms are produced automatically. - Submit — Recruiters review the shortlisted candidates and submit approved profiles to the client. - This kept human recruiters in control of the final decision while AI handled much of the repetitive data processing and document preparation.

What Changed

- The combination of centralized candidate data and AI-assisted matching significantly reduced the time required to identify suitable candidates.

- Candidate matching and filtration decreased from 3–5 days to 2–3 hours.

- Preparing standardized client-ready profiles previously required approximately 30–40 minutes per candidate. With the new system, the same profiles could be generated in seconds.

- The client also reported an approximately 30% improvement in deal win rate, with faster response times helping the agency compete more effectively for time-sensitive recruitment opportunities.

- The system reduced manual work associated with candidate data collection, qualification checks, filtering, anonymization, profile formatting, and application-form preparation.

- As a result, recruiters could spend more time evaluating candidates and working with clients rather than preparing documents and manually moving information between steps.

Business Impact

- The project demonstrated that the value of artificial intelligence in recruitment was not simply about replacing human candidate selection.

- The larger opportunity was reducing the operational work surrounding the recruiter's decision.

- Cogya used AI to help the agency identify relevant candidates faster, structure fragmented candidate information, protect candidate confidentiality, generate consistent client-ready profiles, and respond more quickly to urgent client opportunities.

- Human recruiters continued to evaluate candidates and make final submission decisions. The AI system accelerated the work around those decisions.

Key AI Capabilities

- AI Candidate Matching — Evaluates candidate information against role requirements and helps identify relevant profiles.

- Candidate Ranking — Prioritizes candidates using selected qualification criteria.

- Automated Anonymization — Removes personal identifiers while preserving relevant professional information.

- Structured Candidate Data — Consolidates candidate information into a consistent format for analysis and matching.

- Automated Profile Generation — Produces standardized client-ready application forms from structured candidate information.

- Dynamic Filtering — Allows recruiters to adjust qualification criteria when client requirements change.

The Cogya Approach

- Cogya started with the operational bottleneck rather than the AI model.

- The core problem was the amount of time recruiters spent moving candidate information through disconnected manual steps before a qualified profile could reach the client.

- The solution connected candidate data, recruitment criteria, AI matching, anonymization, and document generation into one custom AI system while keeping recruiters responsible for final candidate decisions.