OpenJobs AI / Before & After
Visual strategy page

From one AI recruiter product to the platform layer for AI-native hiring.

The old story was a recruiting application. The new story is a stack: platform, APIs, HR data, and OpenClaw skills that other agents can plug into.

Before AI Recruiter One application
After Platform + Skills Many agents / many surfaces
Original site 7 days vs 45-day recruiting cycle claim
Platform 99.9% API uptime
Platform 2.4M+ jobs indexed
Platform 180M/mo API requests
The shift in one glance

Same company. Bigger layer.

Before

Application narrative

👥
Buyer Hiring teams
⚙️
Form Single product UX
⏱️
Promise Hire faster
📈
Value Efficiency outcomes
Evolution
After

Infrastructure narrative

🧠
User Agents + builders
🔌
Form Platform + APIs
🧩
Distribution Installable skills
🌐
Value Infrastructure leverage
Three visible layers

Product, platform, and agent distribution.

POST /v1/skills/parse-resume
99.9%Uptime
2.4M+Jobs
180M/moRequests
Unified Recruitment API
AI Recruiting Skills
MCP for HR Data

Infrastructure layer

Capability map

What becomes visible in the new stack.

People Search
Profile Lookup
Candidate Match
Jobs Search
Scholars Search
Talent Analytics
Contact Unlock
Layered architecture

How the new story compounds.

01

Application proof

Real recruiting workflows validate the wedge.

02

Reusable intelligence

Search, match, ranking, and data become primitives.

03

Platform distribution

APIs + skills unlock many AI-native products.

One-line takeaway

OpenJobs AI started as an AI recruiter. It is becoming the stack behind AI recruiting.