FR Book 30 min

Home / Client cases / Matching platform

Engineering consultancy · recruitment and placement

A matching platform built on the firm's own framework.

A firm that places engineers with industrial clients wants to handle more inbound requests and a larger business volume. AI reads the CVs, maps them to its skills framework and matches profiles with client needs.

15field interviews before the first line of code: business managers, consultants, clients
≈ 1,100skills in the framework the AI uses to classify each CV
1 to 4 centsthe cost of analysing one CV, measured in trials
The flow
  1. CV uploadedThe profile fills itself in, then availability and mobility.
  2. ClassificationExperience and skills mapped to the firm's framework.
  3. Technical exerciseTrade-specific questions, graded by the AI.
  4. MatchingProfiles matched to needs, by the firm's rules.
  5. RecruiterAssesses, moves the stage; follow-ups go out on their own.
From the CV to a ranked profile for a client need.

The context

The firm places engineering consultants with industrial clients. It wants to handle more inbound requests and a larger business volume. Fifteen field interviews set the diagnosis: business managers juggling CRM, spreadsheets and billing tools, a database search limited to one keyword, skills files reformatted by hand, applications left waiting.

What was built

  • Candidate space: one link per job offer; the uploaded CV fills in the profile, then availability, mobility and a technical exercise specific to the trade. The candidate leaves with a skills passport and can follow their stages.
  • Client space: the need expressed through a guided flow, which becomes a structured requirement sheet.
  • Recruitment space: a six-stage application tracker, rules for follow-ups and stage changes, a ranking of profiles per offer, the recruiter's assessment, the history of every change, duplicate detection.
  • The website, which the team edits on its own.

What the AI does

  • It reads a CV and maps experience and skills to the firm's framework (around twenty trades).
  • It asks and grades technical questions per trade, with a constrained vocabulary approved point by point by the firm.
  • It matches profiles and needs according to weighting rules set by the firm: major or minor gap, CV freshness, recruiter's assessment.
  • It sources external profiles, after benchmarking nine tools, for about one cent per profile.
Ranking for a need · methods engineerFictional example

Profile 1 · 92%

Tradematch
Skills14/16
CV freshness8 months
Minor gap: mobility

Profile 2 · 74%

Tradematch
Skills9/16
CV freshness1 month
Major gap: certification
Fictional data. Weighting rules are set by the firm.

How

One month of field work and prioritisation, then a build in blocks delivered every week and reviewed with the project lead: candidate intake, client space, website, recruitment tracker, matching. Code, hosting and database were transferred to the firm's own accounts.

Where the project stands

The recruitment tracker has been live since early November and the first real candidates go through the platform. Matching relevance is being validated on real placements, with an evaluation grid proposed by the firm.

Further reading