ScoutHiring Assistant
An AI agent that screens resumes against your actual requirements, schedules interviews, tracks candidates through pipeline stages, and learns from every hiring decision you make. The more you hire, the better it gets.
The Problem
Hiring is a funnel. Most of it is plumbing.
You post a job. You get 200 applications. Maybe 15 are worth reading. But you have to open all 200 to find those 15 — and somewhere between resume 80 and resume 120, your attention starts to drift. Good candidates get lost in the pile.
The screening problem is obvious, but it's only the beginning. After you identify candidates worth talking to, you need to schedule interviews across multiple calendars, send confirmations, track who's at which stage, collect feedback from interviewers, and make decisions before your top picks accept other offers. Each step is a coordination task that eats hours.
ATS platforms help with tracking but not with judgment. They'll tell you a resume contains the keyword "Python" but not whether the candidate's actual experience matches what you need. They automate the inbox but not the thinking. And they certainly don't remember that last time you hired for this role, candidates from certain backgrounds consistently outperformed the ones who looked best on paper.
Scout handles the entire hiring funnel — from initial resume screening through offer stage — with persistent memory that retains your criteria, your preferences, and the outcomes of past decisions. It screens like someone who's worked with you for years, not like a keyword matcher seeing your job description for the first time.
How It Works
Screening that learns what you actually want.
Scout runs on a Sonnet-class model for nuanced evaluation of experience, writing quality, and role fit. Here's the pipeline:
Before screening begins, Uniform works with you to build a detailed requirements model — not just "5 years of experience" but what kind of experience matters, which skills are truly essential vs. nice-to-have, and what signals in a resume predict success in your specific environment. This model persists and refines over time.
Every incoming application is evaluated against your requirements model. Uniform doesn't just keyword-match — it reads for relevance, progression, and role fit. Each candidate gets a structured assessment with specific reasons for the recommendation. You review the agent's reasoning, not just a score.
For candidates who pass screening, Uniform handles scheduling — checking interviewer availability, sending calendar invites, confirming with candidates, and handling reschedules. It manages the logistics so your team focuses on the conversations, not the coordination.
Every candidate is tracked through your stages — applied, screened, phone screen, interview, offer, hired or passed. Uniform surfaces candidates who've been stuck at a stage too long, flags when top candidates might be at risk of dropping off, and keeps the pipeline moving.
When you hire someone — or pass on them — Uniform captures why. Over time, it builds a model of what actually predicts success in your organization. The screening criteria for your next hire are informed by the outcomes of your previous ones. This is institutional knowledge that usually lives in one person's head.
The OS Underneath
More than a model. An operating system.
Scout runs on Montebelle's agent operating system — infrastructure that turns a language model into a persistent hiring partner with institutional memory.
Hiring Memory
Uniform retains everything about your hiring process — role requirements, screening criteria, interviewer preferences, past decisions and their outcomes. When you open a new role similar to one you filled last year, the agent starts with calibrated criteria instead of a blank slate. This is organizational memory that survives turnover.
Bias Verification
The OS monitors screening patterns for consistency. If the agent's recommendations start skewing in ways that don't align with your stated criteria — favoring certain backgrounds, overweighting specific keywords, drifting from the requirements model — it flags the drift. The goal is screening that's consistent, explainable, and aligned with what you actually want.
Fleet Learning
When the Montebelle fleet discovers better screening approaches — more predictive evaluation criteria, improved scheduling coordination, failure patterns in candidate communication — those improvements distribute across the network. Your hiring agent benefits from collective intelligence while your candidate data stays completely confidential.
Ready to hire faster without lowering the bar?
Scout is one configuration of the Montebelle HR agent. Your version gets built around your roles, your evaluation criteria, and your hiring workflow.
Let's TalkFixed price. Two to four weeks. You own the agent.