Preparing for career conversations
Gives managers and talent advisers a ranked set of internal opportunities grounded in the employee’s experience and development needs. Each recommendation explains the capability the role could help build.
— Talent & Leadership
Reads a leader's assessment evidence and career history against the roles open inside the business, then ranks the internal moves that would stretch the right capability, each with the development rationale behind it.
1–2 weeks → ~25 minutes
For a typical multi-document review workflow
No coding required
— USE CASES
Gives managers and talent advisers a ranked set of internal opportunities grounded in the employee’s experience and development needs. Each recommendation explains the capability the role could help build.
Assesses available roles against an employee’s appetite for growth and areas for development. The rationale distinguishes a purposeful stretch from a move that mainly repeats existing experience.
Provides a consistent basis for comparing roles with different demands and development potential. The shortlist makes the case for each recommended move explicit rather than relying on job titles or familiar career paths.
Connects development needs identified in assessment and performance evidence to practical internal career options. The recommendations help talent teams discuss role moves as a route to building specific capabilities.
— HOW IT BEHAVES
The mechanics behind this specific template — what it reads, what it calculates, and where a human stays in the loop.
All of your org data, role documentation and headcount exports is processed as one set, so patterns across documents surface instead of being read one file at a time.
Current external sources on the organisation in scope are researched during the run rather than recalled from training data, and every source travels with the output.
Findings on the organisation in scope are written up as a document that reads like professional output, with each claim tied back to a role.
Internal mobility decisions can favour familiar career paths or immediate vacancies over meaningful development. In practice it shows up as preparing for career conversations: gives managers and talent advisers a ranked set of internal opportunities grounded in the employee’s experience and development needs. Each recommendation explains the capability the role could help build. The value sits in the rigour, not the typing — yet the rigour is exactly what gets traded away when there is only 1–2 weeks of capacity for it.
As a Skill, the work is already sequenced. You bring the evidence, and the run produces evidence-based profile of experience, growth appetite and development needs plus ranked shortlist of available internal moves. The criteria, ordering and review points that make the answer trustworthy are encoded in the Skill itself — which is the difference between a structured method and a prompt someone pastes in. In effect, 1–2 weeks of senior time compresses into ~25 minutes — and the output is comparable across clients, quarters and colleagues instead of shaped by whoever ran it.
Internal Mobility Matchmaker 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.