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One standard for every recruiting team: we helped modernize SHL's talent assessment.

SHL combines people science, psychometrics and AI to help global enterprises identify top talent, with assessments and interview technology used by more than 10,000 businesses worldwide.

Wildstream partnered with SHL's scientific and product teams to modernize legacy tools, reduce manual handoffs and build AI-driven systems, including NLP and scoring models for consistent candidate evaluation.

SHL
  • Applied AI

Same score, any region

Recruiting teams in every region receive consistent candidate scoring, which leads to more standardized hiring decisions

Interviews and role-plays

Candidate responses are evaluated in both interviews and role-play scenarios, covering what people say and how they act

Scientific rigor kept

The AI-driven systems were built with SHL's scientific teams, keeping the rigor of its assessment science intact at scale

Applied AI

Consistent Candidate Scoring

Hiring outcomes differ between recruiting teams and regions, leading to inconsistent decisions. Large organizations often see this when recruiting teams in different regions assess the same roles. SHL, which combines psychometrics and AI to help global enterprises identify top talent, also needed technology that would keep up with growing client expectations and more complex internal processes.

Same score, any region

Recruiting teams in every region receive consistent candidate scoring, which leads to more standardized hiring decisions.

Interviews and role-plays

Candidate responses are evaluated in both interviews and role-play scenarios, covering what people say and how they act.

Scientific rigor kept

The AI-driven systems were built with SHL's scientific teams, keeping the rigor of its assessment science intact at scale.

What we did

NLP and scoring models evaluate candidate answers in interviews and role-play scenarios, giving every team the same standardized scoring.

Sponsored by SHL's Chief Innovation Officer, Wildstream implemented natural-language processing and scoring models that evaluate candidate responses in interviews and role-play scenarios. The work was part of a wider partnership with SHL's scientific and product teams to modernize legacy tools, reduce manual handoffs and build AI-driven systems for both operational teams and client-facing users.

How it works
  1. Candidates answer interview questions and role-play scenarios
  2. NLP analyzes the content of each response
  3. Scoring models rate the responses against one shared standard
  4. Every recruiting team receives the same standardized scores
  5. Hiring decisions are made on a consistent basis
Key capabilities

Response analysis

Natural-language processing reads candidate answers in detail, turning free-form responses into structured evidence for scoring.

Standardized scoring models

The same scoring models apply to every recruiting team, so a candidate's result does not depend on who reviews it.

Role-play evaluation

Responses in role-play scenarios are scored alongside interviews, showing how candidates handle realistic work situations.

Technology
  • Natural-language processing
  • Scoring models
Impact

One scoring standard for interviews and role-plays, applied the same way by every recruiting team

Fairer hiring decisions

Candidates are judged against one standard wherever they apply, making hiring outcomes more consistent and more fair.

Faster client onboarding

SHL's modernized, automated foundation improved internal efficiency and supported faster onboarding of new enterprise clients.

Ready for what comes next

Replacing outdated systems with a flexible foundation laid the groundwork for continued innovation in talent assessment.

Bring us a challenge like this

Tell us where your operations still depend on manual work, and we will tell you what is worth building first.