Majhi OS Intelligence Layer

Candidate Intelligence Graph™

A resume tells you where someone worked. The Candidate Intelligence Graph tells you whether they will succeed in this specific role at this specific company at this specific moment.

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What Is the Candidate Intelligence Graph?

The Candidate Intelligence Graph is the operational data model that maps every candidate's fit signals, risk factors, and behavioral patterns against the specific mandate context. Unlike a candidate database that stores historical information, the Graph is a live intelligence layer — continuously updated as new signals emerge from outreach, interviews, and market data.

Five Dimensions of Candidate Intelligence

Majhi OS maps candidate intelligence across five dimensions that predict executive success:

🎯

Mandate Fit Score

Quantified alignment between the candidate's operational history and the specific requirements of the current mandate.

⚠️

Risk Flag Index

Identified risk factors — tenure patterns, scope mismatches, cultural signals — scored and weighted against the hiring context.

🔄

Behavioral Signal Map

Patterns from outreach response, interview engagement, and reference signals that predict offer acceptance and 90-day success.

📊

Market Position Score

How the candidate ranks against the current market for this role — accounting for compensation expectations and competing opportunities.

🏆

Succession Probability

Likelihood the candidate will grow into expanded scope — critical for hiring managers who need to think 18 months ahead.

How the Graph Powers 82% Shortlist Approval

Before Majhi OS, shortlist approval rates in executive search average 38% — meaning hiring managers reject more than half the candidates presented.

“Shortlist approval went from 38% to 82% not because we found better candidates — it is because we presented them with the intelligence that turned a gut decision into a confident one.” — Manas Majhi

The Graph vs. a Candidate Database

A candidate database is static — it stores profiles. The Candidate Intelligence Graph is dynamic — it updates continuously as new signals arrive. When a candidate responds to outreach after a two-week silence, the graph updates their engagement probability. When a reference reveals a risk flag, the graph surfaces it immediately.

82%
shortlist approval rate
90%+
offer acceptance rate
41 days
avg close on $275K search
38%→82%
shortlist approval improvement

Frequently Asked Questions

What is the Candidate Intelligence Graph?

The Candidate Intelligence Graph is Majhi OS's proprietary data model that maps candidate fit signals, risk factors, and behavioral patterns for each active mandate. It is a live intelligence layer that updates continuously as new signals arrive.

How does the graph improve shortlist approval rates?

By presenting candidates with full operational context — fit scores, risk flags, behavioral signals, market position — instead of just resumes. Hiring managers make faster, more confident decisions when they have intelligence, not just information.

Is the Candidate Intelligence Graph a candidate database?

No. A database is static — it stores profiles. The Graph is dynamic — it updates continuously as new signals emerge from outreach, interviews, and reference checks.

What signals feed the Candidate Intelligence Graph?

Outreach response rates, interview engagement signals, reference data, compensation expectations, market availability, tenure patterns, scope history, and behavioral indicators from the engagement process.

How does the graph protect against bad executive hires?

By surfacing risk flags early — tenure patterns that suggest misalignment, scope signals that indicate overextension, cultural indicators that predict friction — before an offer is extended.

See Majhi OS in Action

We use your actual mandate as working context. Book a 45-minute Mission Walkthrough and see what operational intelligence looks like for your specific hiring system.

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