AI in recruiting was supposed to find better candidates faster. Instead, most systems are optimizing for volume reduction — and eliminating top talent in the process. We help organizations audit, redesign, and fix the way AI is deployed across their hiring funnel.
Most recruiting consultants come from HR or HR tech. Our principal has spent 20+ years in senior operations leadership at organizations like Microsoft and Meta — where large-scale AI-driven recruiting is a daily operational reality — and has directly experienced the candidate side of these systems as well. That perspective, combined with deep AI workflow expertise, lets us identify the gaps that internal teams are too close to see.
Every engagement is scoped and delivered as a fixed-fee project. We work directly with talent acquisition leaders, HR operations, and people analytics teams — producing written, actionable deliverables your team can implement immediately.
Pull the actual filter logic, keyword requirements, scoring weights, and minimum thresholds out of the black box. Map what's being eliminated versus what's getting through — and compare against actual hire quality data.
Audit current job descriptions for credential inflation, experience window mismatches, gendered language, and over-specified requirements — then rebuild them around what the role actually demands versus what the last person happened to have.
Map the full applicant experience from job posting through first interview. Identify where AI-driven friction, dehumanizing interactions, and poor design are causing top-tier candidates — the ones with options — to abandon the process.
Redesign chatbot and pre-screening workflows to reduce false negatives while maintaining efficiency — replacing rigid binary logic with structured assessments that capture nuance and don't penalize candidates with non-linear backgrounds.
Analyze screening outcomes across demographic groups for patterns consistent with disparate impact — both as an ethical obligation and as a compliance requirement under EEOC guidance and emerging AI employment legislation.
Replace credential and keyword-based filtering with explicitly defined competency frameworks — built around what a successful candidate in each role actually needs to demonstrate, not the proxies that have accumulated over years of hiring inertia.
Train recruiting teams to use AI as a high-quality assist rather than an autonomous decision-maker — covering prompt engineering for job descriptions, critical evaluation of AI screening outputs, and building human oversight into key decision points.
AI recruiting problems don't sit in a single department. They live at the intersection of HR, IT, legal, and operations — and solving them requires someone who can talk credibly to all of them. We work across that full landscape.
VPs and Directors of TA who know their funnel metrics look fine but suspect the system is filtering wrong — and need an independent diagnosis to know where and why.
The teams managing day-to-day ATS administration who have inherited filter configurations they didn't design and don't have the standing to challenge without external data to back them up.
Analytics functions that have the data to answer these questions but haven't been asked — or haven't had the framework to connect screening behavior to downstream hire quality outcomes.
Legal teams navigating the rapidly evolving landscape of AI employment law — NYC Local Law 144, Illinois facial analysis rules, and emerging state legislation — who need an operational audit to understand their current exposure.
Growing companies that adopted ATS and pre-screening tools early and have been running them on default settings — without the internal resources to audit whether they're working as intended.
Organizations building AI recruiting tools who need domain expertise to evaluate model outputs, stress-test systems against real-world edge cases, and ensure their products aren't reproducing the problems they're designed to solve.
A deep look at why AI recruiting is producing the opposite of its intended outcome — from ATS keyword traps and credential inflation to the self-selection dynamic that sends the best candidates to your competitors, and what organizations getting it right are doing differently.
Read the article →Most organizations have never audited their screening logic against real outcomes. We'll tell you what your system is optimizing for — and whether that's actually what you want.