Compare vendor options before an IT purchase
Research and evaluate competing solutions against your actual requirements before committing to a purchase.
Build a Copilot Studio agent that ranks candidates against a job's actual requirements to speed up the first screening pass.
Faster time-to-shortlist for recruiters without lowering candidate quality at the top of the funnel.
Resumes carry candidates' personal information (contact details, full work history). Restrict the agent's knowledge source (step 2) to the active requisition's candidate pool, not a shared company-wide resume repository, and limit who can see individual scores to recruiters with a legitimate need.
The apps run in this order.
Rewrite the job description as a numbered checklist of concrete, verifiable items — "5+ years SQL," "active PMP certification," "built financial models in Excel" — and cut anything like "strong communicator" or "team player" that can't be confirmed from a resume's text.
Every item on this list should be something a human reviewer could also check and agree on; if two recruiters would score it differently, the agent will too.
In Copilot Studio, have the agent read each candidate profile against the requirements checklist and return a score with the specific evidence from the resume backing each matched requirement.
Prompt idea:
Score this candidate against the requirements for the Senior Data Analyst role: 5+ years SQL experience, Power BI proficiency, and a degree in a quantitative field. For each requirement, state whether the resume shows evidence of it and quote the relevant line.
The agent's output is a ranked, evidence-backed shortlist for a recruiter to review — it should never auto-reject or auto-advance a candidate without human sign-off, given the legal exposure around biased or opaque hiring decisions.
Export a batch of scored candidates into an Excel Table and sort by score against fields like school name, employment gaps, or anything else that correlates with protected characteristics.
If top scores cluster suspiciously around one pattern unrelated to the stated requirements, that's a signal the checklist or the agent's reading of it needs adjustment, not something to wave off as coincidence.
A ranked shortlist of candidates against a specific role's requirements, with the reasoning for each ranking stated.
A requirement phrased many different ways across resumes ("5+ years SQL" vs. a project description that implies it) needs reading comprehension to score with evidence — keyword matching alone misses the paraphrased cases.
Non-AI alternative: A basic keyword filter can pre-screen for an exact-phrase requirement like a named certification, but evidence-backed scoring against requirements stated in varied language needs the agent's comprehension.
Research and evaluate competing solutions against your actual requirements before committing to a purchase.
Use a Case and Precedent Analysis Agent to process a large volume of legal documents, surface usable arguments, and draft a first-pass brief.
Workflows like this tend to raise real governance and licensing questions once more than one person is using them — that's exactly what we help with.