Fast shortlisting
Get from a pool to a ranked shortlist with written rationale in a single run.
— Talent & Leadership
Ranks a candidate pool on evidence, takes the top slice, and writes the rationale explaining why the shortlist fell the way it did.
1 day → ~15 minutes
For one complete, review-ready pass
No coding required
— USE CASES
Get from a pool to a ranked shortlist with written rationale in a single run.
Show the evidence behind the order so the ranking can be interrogated.
Apply the same ranking basis to every role you run.
— HOW IT BEHAVES
The mechanics behind this specific template — what it reads, what it calculates, and where a human stays in the loop.
Skills and requirements are read out of CVs, applications and interview notes as structured data rather than inferred from job titles.
Findings on the candidate pool are written up as a document that reads like professional output, with each claim tied back to a candidate.
Candidates are compared on the same dimensions, which makes differences meaningful rather than impressionistic.
The run works from CVs, applications and interview notes you supply, so conclusions about the candidate pool are anchored to your evidence rather than general model knowledge.
Every talent & leadership team needs shortlist & rank — and almost none of them do it the same way twice. In practice it shows up as fast shortlisting: get from a pool to a ranked shortlist with written rationale in a single run. It is the kind of work that decides whether a recommendation survives scrutiny — and the kind that quietly eats 1 day of senior time whenever it comes round.
As a Skill, the work is already sequenced. You bring the evidence, and the run produces an evidence-based ranking of the pool plus the top slice as a shortlist. The judgement is built in — how items are broken up, what standard they are held to, and where the run stops for a human review. Net effect: 1 day down to ~15 minutes, no drift between runs, and every conclusion traceable back to the evidence behind it.
Shortlist & rank exports as a structured SKILL.md file and is MCP-ready, so the same method runs in ChatGPT, Claude, Copilot or your own AI products. Adapt it to your methodology, and the intelligence stays yours — not locked to one vendor.
Builds evidence-backed employee skills profiles within HR systems, mapping documented experience to the organisation’s skills catalogue and assigning proficiency levels using consistent rules.
Assesses how clearly people explain their technical work against a consistent four-level rubric, producing a human-approved report with quoted evidence behind every score.
Reveals how organisational culture is lived through anonymous employee accounts, producing an evidence-backed diagnostic of shared themes, differences between functions and gaps between values and practice.
Turns a high-potential's assessment evidence into an acceleration plan weighted to real experience and exposure, naming the stretch assignments, mentors and programmes that will compound fastest.
Builds a calibrated, reusable benchmark from source material so every later screen, shortlist or review is graded against the same bar.
Screens candidate evidence against a saved Blueprint, applying the same calibrated bar and traceable reasoning to every applicant.