For coaching teams & outplacement providers

    Start every coaching sessionwith the candidate context already prepared

    DraftApply reviews applications, job descriptions, submitted CV versions, fit assessments, and available outcomes before the session begins.

    Your coach receives one evidence-backed view of the candidate's targeting, recurring strengths, repeated gaps, CV strategy, and three next priorities.

    The evidence is prepared before the session. The coach keeps the judgment.

    Twelve applications. Three CV versions. Two interviews. Where is the pattern?

    A candidate has submitted twelve applications using three CV versions across four types of roles. Two reached interviews, several were rejected.

    Before offering useful advice, the coach has to reconstruct the candidate's application strategy from scattered documents—answering three questions first:

    • ?What is the candidate actually targeting?
    • ?Is the repeated problem the profile, the CV, or the target roles?
    • ?Which advice should be prioritized now?

    DraftApply prepares that analysis before the session begins—and keeps every conclusion traceable to the applications behind it.

    A preparation layer for better coaching decisions

    Candidate materials
    Evidence-backed review
    Coach judgment
    Clear next action

    An example candidate review

    One evidence-backed view of the candidate's application strategy across jobs, CV versions, recurring gaps, and available outcomes—ready before the candidate joins.

    Candidate review
    Candidate A · 12 applications · Mar 1 – May 30
    Illustrative portfolio using anonymized sample data
    Evidence-backed

    Role families

    • Applied AI (finance)
      5 apps · strongest track
    • GenAI Research
      4 apps · weaker alignment
    • Platform Engineering
      3 apps · exploratory

    CV strategy

    One Applied AI CV reused across all three role families.

    Same positioning applied to research roles where publications are expected.

    Next actions

    1. 1.
      Prioritize finance AI roles
    2. 2.
      Verify deployment evidence in CV
      Gap across 2 applications
    3. 3.
      Decide whether research remains a target
      Requires coach judgment
    Finding

    The Applied AI CV was reused for research roles.

    Why it matters

    The research roles emphasized publications and formal experimentation, while the submitted CV emphasized workflow implementation.

    Evidence
    • ·GenAI Researcher job description
    • ·Applied AI CV used for that application
    Every material finding links back to the applications and source types that support it—job descriptions, submitted CVs, fit assessments, statuses, and outcome notes.

    Standardize preparation across the team without forcing every coach into the same final judgment.

    What that repetition costs the business

    The effort is easy to overlook because it feels like normal preparation. But as the team grows, it shows up in three places.

    Coaching expertise goes to fact-gathering

    Coaches spend valuable preparation time reconstructing information instead of interpreting it and deciding what the candidate should do next.

    Preparation varies by coach

    Different coaches emphasize different details, so review quality and recommendations depend too heavily on who happens to open the file.

    Growth means more hours

    Every additional candidate adds more manual preparation, making capacity harder to increase without adding coaching hours.

    What the review includes

    Inputs

    • Applications
    • Job descriptions
    • Submitted CV versions
    • Fit assessments
    • Statuses and available feedback

    Review output

    • Role-family targeting
    • Recurring strengths and gaps
    • CV usage strategy
    • Outcome signals
    • Three prioritized actions
    • Human review questions

    Why coaching teams use it

    Manual preparation limits how many candidates each coach can support. A prepared review changes that.

    Reduce preparation time

    Coaches begin with a structured review instead of opening every document manually.

    Standardize candidate reviews

    A consistent review baseline ensures the same core questions are considered for every candidate, while coaches retain final judgment.

    Make recommendations traceable

    Findings can be traced back to the applications that support them.

    Increase coach capacity

    Less repetitive preparation creates more capacity for actual coaching work.

    A structured evidence layer can also help less experienced coaches prepare cases while senior coaches retain oversight.

    Designed to support coaches—not replace them

    Experienced coaches should spend their time applying judgment—not reconstructing information that already exists. DraftApply does not make final career decisions. It does not know which direction the candidate personally values, what trade-offs they'll accept, what experience is missing from the documents, or whether a secondary career track is strategically important.

    These decisions remain with the coach and candidate. DraftApply prepares the portfolio, identifies patterns, and makes the evidence easier to review.

    Pilot data handling

    Anonymized or synthetic portfolios are supported. Pilot participants agree in advance on what data is provided, how long it is retained, and how it is deleted after evaluation.

    Anonymized or synthetic data accepted
    Retention and deletion agreed before the pilot
    No requirement to connect or replace existing systems

    The pilot

    Send one anonymized candidate portfolio. We prepare the review and compare it with how your team would assess the same case.

    Pilot includes

    • One or more candidate portfolio reviews
    • Comparison with the coach's existing methodology
    • A structured feedback session
    • No need to replace current systems
    • Anonymized or synthetic data accepted

    In return, we ask your team to identify what is useful, misleading, missing, or inconsistent with your review process.

    For a pilot, DraftApply prepares the review from the candidate materials you provide—no integration or system change required.

    Built for career-coaching companies, outplacement providers, employability programmes, and university career services that already receive candidate CVs, applications, and job descriptions but still review them manually.

    Every new candidate should add coaching value—not another stack of documents to compare.

    Prepare the evidence before the session

    Give coaches a structured view of the candidate's application history—so the session can focus on decisions, priorities, and progress.

    View an example review

    Evidence-backed candidate portfolio reviews for job coaching teams.