We audit your hiring funnel to determine whether your systems — human or AI-driven — are producing high-signal, defensible decisions or exposing your company to costly inefficiency and compliance risk.
The Tipping Point Signal Model™ evaluates your hiring system across the dimensions that actually determine whether you're making good decisions — not just fast ones. Each dimension is scored 1 to 4. The composite tells you where you stand and what it's costing you.
The audit is designed to deliver a complete picture in days — with no templates to fill out ahead of time, no workshops to schedule, and no 80-page deck at the end. One intake call. Your own data. A clear scorecard.
A structured 60-minute guided conversation with your TA or HR lead. We navigate to your data together — live in your ATS — so you don't need to prepare anything in advance.
Your funnel data runs through the Tipping Point Signal Model™ — all four dimensions scored, the signal ratio calculated, and findings documented with specificity rather than generality.
A clean, executive-ready report: four dimension scores, a composite rating, specific findings for each dimension, and prioritized recommendations with effort and impact ratings.
A focused debrief to walk through findings, answer questions, and discuss what remediation looks like — with or without ongoing Tipping Point involvement.
Most companies have added AI to their hiring process without ever asking whether it's improving the decisions being made — or just accelerating the ones they were already making badly. The two feel identical until you measure the signal ratio.
AI hiring tools optimize for what they were trained on. If they were trained on your historical hires, they're optimizing to replicate your past decisions — including your past biases, your past sourcing constraints, and the candidates you happened to find. That's not signal. That's amplified pattern-matching.
The audit doesn't tell you whether to use AI. It tells you whether the AI you're using is making your hiring better or just faster — and whether you can defend every decision it touches when someone asks.
Each option includes the full audit methodology — the Signal Scorecard across all four dimensions with a prioritized recommendations report. The difference is what happens after delivery.
The complete audit: four-dimension scoring, signal ratio calculation, regulatory exposure summary, and prioritized findings with a 45-minute readout. Everything you need to know what's wrong and what to fix first.
Everything in the Signal Audit, plus hands-on redesign of the elements the scorecard identifies as broken. Job description rewrites, screening criteria builds, AI oversight protocols, and an implementation roadmap with owners and timelines.
Quarterly signal re-calibration plus ongoing advisory access as your hiring system evolves — new tools, new markets, new roles. Includes monitoring of emerging AI hiring regulations as they come into effect.
Most companies using AI in hiring don't know what their vendor contracts actually say about who owns the risk when a decision is challenged. The answer is almost always: you do.
U.S. jurisdictions are moving quickly to regulate automated employment decision tools. New York City, Illinois, and Colorado have already passed AI hiring statutes. The EEOC has clarified that employers — not vendors — are responsible for adverse impact from AI screening tools under Title VII.
The companies that will navigate this well are the ones that can already answer: what does our AI actually do, has anyone reviewed it for bias, and can we document every decision it touches. Most can't. That's what the Defensibility dimension of the audit measures — and what the recommendations address.
Requires annual independent bias audits of Automated Employment Decision Tools before use in hiring. Employers — not vendors — bear audit and disclosure obligations.
Prohibits AI-analyzed video interviews without candidate consent. Requires annual bias reporting for employers using AI to evaluate candidates via video.
Requires impact assessments, record retention, and candidate notification for AI use in consequential employment decisions. Employer accountability — not vendor accountability.
EEOC holds employers responsible for adverse impact from AI tools under Title VII. Selection rates for protected groups must not fall below 80% of the highest-performing group — including AI-assisted selection.
A short call is usually enough to scope the engagement. Reach out and we'll find out if the timing is right.