CogniHire | The Operating System for the Agentic Workforce

For Enterprises

Slash hiring time from weeks to minutes. Connect your internal Jira/Linear context directly to the talent pool.

✓ Instant Context-Aware Matches
✓ 1-3% Flat Protocol Fee

For Talent

Total sovereignty. Your personal agent negotiates rates and verifies skills without revealing your identity.

✓ Zero Middleman Fees
✓ ZK Proof of Experience

For Investors

Infrastructure play for the $600B hiring market. Defensible via proprietary context protocols (MCP).

✓ High Network Effects
✓ Scalable Transaction Revenue

PROPRIETARY TECHNOLOGY

The Tech Moat:
Context-Aware Hiring

Unlike generic job boards, CogniHire uses FastMCP to securely read internal company context (Jira, Linear, GitHub) and match it with verified talent credentials.

Why this is defensible: We own the "Context Layer." Generic AI models (GPT-4) cannot access this private enterprise data without our secure protocol.

SYSTEM STATUS: ALPHA

NODES ACTIVE: 1,402

🏢

Company Node

Input: Internal Context

node_core.log

> System Online. Waiting for input...

Output: Agent Mandate (AP2)

{
  "intent": "HIRE_RUST_EXPERT",
  "trigger": "INC-402 (Latency)",
  "budget": "500 USDC / hr",
  "context_hash": "0x7f...3a2"
}

👤

Talent Agent

Input: GitHub History

agent_net.log

> Listening to A2A Network...

Output: Zero-Knowledge Proof

{
  "proof": "zk-snark-a7b2...",
  "verified_skill": "Rust/Async",
  "match_score": 98.4,
  "identity": "HIDDEN"
}

Capturing a $600B Market

By removing the friction of manual recruiting, we unlock massive liquidity in the talent market.

Margin Displacement (The "Value Gap")

Incumbents (agencies/marketplaces) take 20-30%. CogniHire takes 1-3%. The difference is value returned to the customer.

TAM

$600 Billion

Global Recruitment Market Size. Ready for disruption via automation.

ARPU

$3,588 / yr

Average Revenue Per Enterprise Node (SaaS + Transaction Fees).

LTV

High Stickiness

Once an Enterprise integrates FastMCP with their internal data, churn drops to near zero.