Leveled AI

Service

Hiring Systems That Surface the Five People Worth Calling

A job post that works becomes its own problem. Two hundred applications arrive, most are nowhere close, and the good candidates take another offer while somebody works through the pile at night. Reading faster is not the fix. A process that sorts before a human opens anything is.

Intake that collects what you actually screen on

Resumes are a bad screening format and everybody keeps using them anyway. We build an application flow that asks the three or four things you really decide on (tools they have used, a situation they have handled, availability, comp expectations) and stores the answers as structured fields instead of prose. The candidate gets a form that takes six minutes. You get a table you can sort.

Scoring against your criteria, with the reasoning attached

Every applicant gets scored against a rubric you write, and the score comes back with the specific lines from the application that produced it. That last part matters. A number with no explanation is something nobody trusts by the second week, and a rubric you can argue with is a rubric you can fix. The system ranks and flags. A person decides who gets an interview, every time.

Trial tasks that run without babysitting

The strongest signal in hiring is watching somebody do a small version of the job. It also creates a scheduling mess: sending the task, tracking who finished, chasing the ones who went quiet, collecting the output somewhere reviewable. We automate that loop, so running paid trials with eight candidates costs about the same effort as running one, and the finished work lands in one place with a timestamp.

Keeping candidates warm while you decide

Good applicants accept somewhere else during the week your team spends deliberating. We set up status updates that go out on their own, scheduling links tied to your real calendar, and a short honest note to everyone you pass on. It keeps the process from leaking people who were still interested, and it protects your name for the next time you post.

What you actually get

  • An application form built around the three or four things you screen on
  • A written rubric, and scores that show the evidence behind them
  • A ranked shortlist instead of a folder of PDFs
  • Trial task sending, chasing, and collection handled automatically
  • Candidate status updates that go out without anyone remembering

Common Questions

Before you book a call

Does the AI decide who gets hired?
No. It scores and ranks against criteria you write, and it shows the evidence behind each score. A person makes every hiring and rejection decision. That is the only version that is defensible, and the only version that improves, because your corrections feed back into the rubric.
Is automated scoring a legal risk?
It can be, which is why the build keeps a human in the decision and keeps a record of why each candidate scored the way they did. Rules on automated employment decisions vary by state and city and they are still changing. We are not your employment lawyer, and for a high-volume hiring program you should have one read the rubric.
Does this work with our applicant tracking system?
Usually. Greenhouse, Lever, Workable, and similar platforms have APIs we can read from and write to. If you are hiring out of a Gmail inbox and a spreadsheet, we can start there instead.
We hire a few people a year. Is this overkill?
For the scoring piece, probably. The intake form and the candidate communication are still worth it at low volume, because those are the parts that embarrass you when they slip. If the full build does not make sense for your hiring volume, we will say so.

Let's find out if this fits

A 30-minute call, no charge. If we can help, we will show you how. If we cannot, you still leave knowing what to do next.