Monday with Federica, talent acquisition lead at a 120-person manufacturer
A TA lead at a mid-market industrial company opens a Monday morning with two open roles. By Friday she has shipped three Decision Packs to her hiring manager and has a candidate in for a trial. Here's the workflow that replaced two weeks of phone screens.
08:45 — Two roles, one Monday
Federica leads talent acquisition at a 120-person manufacturer near Treviso. The company makes precision components for the automotive supply chain. She has two open roles this Monday: a junior automation engineer (urgent — a customer project starts in seven weeks) and a mid-level production planner (less urgent, but the current planner is leaving in three months).
In her old workflow she'd open Greenhouse, post both roles, and wait for the wave of CVs. By Wednesday she'd have 80–120 applicants for the automation role, of which maybe 8 would be plausible. Then phone screens. Then she'd hand the survivors to the engineering manager.
She doesn't do that anymore for the early-career roles. She opens InTransparency.
09:00 — Smart Search, automation role
She types one sentence into Smart Search:
"Junior automation engineer, comfortable with Siemens PLCs and basic robotics, willing to be on-site near Treviso, ITS or first-cycle laurea fine."
She doesn't write boolean queries. She doesn't configure filters. The AI returns 11 candidates, ranked, with the matching evidence visible for each. Three are from ITS Academies (Padova, Bergamo, Treviso itself). Five are first-cycle engineering students. Three are recent laureati.
The "matching evidence" column is what changed her job. For each candidate she sees the actual project artifacts the AI used to compute the match — not just keywords. She clicks through to two of the ITS profiles to look at their production-cell projects directly. Both are real, working systems. One has a video.
She shortlists 5.
10:30 — Decision Packs
For each shortlisted candidate she generates a Decision Pack. Two pages each, generated automatically:
- Verified skill list with links to artifacts
- Italian grades normalized to a comparable scale
- Personality summary if available
- Employability prediction with visible assumptions
She reads all five in about 35 minutes. She rules out two — one whose project portfolio is mostly mechanical with little controls work, one whose stage was at a company doing logistics rather than manufacturing. She keeps three.
She emails the three Decision Packs to the engineering manager, Lorenzo, before lunch.
11:45 — The planner role, different approach
For the production planner role she takes a different path. The pool of recent graduates with planning experience is thin. She uses Smart Search to scan the verified pool but also queues an alert for new profiles matching the pattern. She'll let it run for a week.
For now she sources two candidates herself by browsing the verified pool's planning category. One looks promising. She adds him to her tracking and moves on.
Wednesday — Lorenzo's reply
Lorenzo replies on Wednesday. He's read all three Decision Packs. He wants to interview two — Marco from Bergamo and Anita from Padova. He says he found the artifact links the most useful part: "I clicked through to Marco's PLC code and could tell in five minutes that he writes structured text the way I'd want him to."
Federica schedules both interviews for the following week. She writes the messages from inside the platform; both go through the candidate's school's Mediation Inbox first and get approved within the day.
Friday — the half-day trial
Marco accepts the half-day trial offer for the following Friday. Anita interviews on Tuesday and is also strong but in a different way — she's a better fit for a more design-heavy role they have open in three months.
Federica logs both interactions in the platform. The audit log captures every touchpoint: search query, shortlist, Decision Pack download, message sent, response, interview scheduled. If her DPO ever asks why a particular candidate was contacted, she can show him in two clicks.
What changed
The total Federica time on the automation role this week: about 4 hours, including reading Decision Packs and writing messages. In her old workflow it would have been about 14, most of it phone screens that didn't lead anywhere.
The hiring manager's time went from "two phone screens minimum before he met anyone in person" to "read three two-page documents and pick the two he wants to see."
That's the platform from a recruiter's seat. The role isn't filled yet. The pipeline to fill it is real, evidence-based, and auditable.