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Feature · 04 of 07

Expand any shortlist in one click.

From a validated candidate, semantic analysis finds nearby profiles on skills, background and career path. Without starting a new search, without missing the hidden gems.

claude.ai · jemmo.similarfound
You
Find me profiles similar to Clément M. whom we validated yesterday.
Claude
I'm calling jemmo.similar on Clément's talent_id.
Jemmo
8 similar profiles — semantic score 78-92%. Stack, seniority, sector aligned.
Three similarity axes

Multi-dimensional. Semantic.

The AI measures similarity across skills, experience and career paths — not just on the resume's keywords.

a.

Semantic skills

Technical embeddings bring React Native and Expo, Postgres and MySQL, Kubernetes and Nomad closer — beyond literal keywords.

b.

Comparable trajectories

Comparison of career progression, scope changes, mission types. To find profiles with a similar trajectory.

c.

Sector and culture

Matching on business sector, company size, organization type. A scale-up profile vs a large group: a different signal.

How it works

From one candidate, eight similar ones.

01.

Select a reference candidate.

Click on a profile you've validated, or ask your AI in natural language — Jemmo identifies the talent automatically.

The source profile becomes the query: its skills, its background, its sector serve as the pivot for the semantic search.

Sélection candidat« Profils similaires à Clément M. validé hier. »
1jemmo.identify · talent_id0.2s
2jemmo.similar · embeddings 1024D1.8s
3jemmo.shortlist · 8 profils prochesinstant
02.

The AI measures similarity.

Technical embeddings (Voyage AI rerank-2.5) compute semantic proximity over 1024 dimensions — not just skills, also context and trajectory.

The scoring includes our exclusive signals: a similar and available profile moves ahead of a similar but barely responsive one.

Compétences
92
Trajectoire carrière
84
Secteur métier
78
Taille entreprise
71
Formation
65
03.

Expand without sacrificing relevance.

Each similar profile arrives with its score, the matching axes and the notable differences. You see what's close, what's distinct.

Backup candidates, coherent teams, diversity sourcing — the feature serves several use cases in one click.

Différences notablesMarie L. · 87% — Stack très proche, secteur fintech vs banque, junior+1 vs senior+2. Bon backup junior.
Use cases

When to look for similar profiles?

The "similar" pattern unlocks sourcing that's impossible with a classic criteria search.

Backup

Candidate plan B

Candidate #1 hesitates or withdraws. In one click, 8 comparable profiles ready to pitch.

"Profiles similar to the candidate validated yesterday for the Lead Data role."
Squad

Coherent team

For a squad that must collaborate, profiles with similar trajectories create less cultural friction.

"3 profiles similar to the tech lead I just hired."
Diversity

Inclusive sourcing

Find profiles with equivalent skills but from different backgrounds — schools, sectors, geographies.

"Profiles similar to X, excluding the same target schools."
Comparison

vs keyword search.

CriterionResume keywordsJemmo similar profiles
Finds profiles beyond keywordsNoYes (semantic)
Measures trajectory1024D embeddings
Weights signalsAvailability + openness included
Diversifies resultsSame words = same profilesVaried trajectories
User effortRephrase every timeOne click
Go further

Related features.

One shortlist hides eight more.

Expand your shortlists in one click. 2-week free trial.