Beta · Free · No card required

A sourcing agent that runs on data your stack can't reach.

Custom GPT agents do keyword overlap on public data. The Glozo Sourcing Agent runs on three proprietary data layers: Skill Graph, Market Value, and Open-to-Offers. It surfaces candidates a GPT wrapper can't.

No card. No demo call. 2 minutes to first run.

Where DIY agents break.

Custom GPT agents speed up the wrong work. They guess at signal that doesn't exist in public data.

01

Keyword overlap, not skill match.

GPT agents read what's written on a profile. Embedding match, keyword overlap. They can't tell one mention of a tech from five years of using it. They guess at depth.

02

Salary fit is a guess.

Custom agents have no compensation data. They guess at whether a candidate fits your budget. Wrong guesses burn outreach credits and time.

03

Reply rate is hope.

DIY agents can read LinkedIn's "Open to Work" badge and not much else. The behavioral signal that surfaces passive but receptive candidates is invisible to public-API agents.

Glozo's sourcing agent runs on the signals your DIY agent can't.

Three signals under every match.

Three proprietary signals shape every match. None come from public APIs. None can be replicated by a GPT wrapper. We surface. You decide.

Layer 01

Skill Graph

A weighted model of candidate skills. The engine reads public sources (LinkedIn, GitHub, and 30+ more) and builds the graph with tenure, project complexity, contribution depth, and company context.

Mention from mastery. Same title, different work, different match.

Layer 02

Market Value

A per-candidate salary estimate. Built by a statistical model trained on 10M+ market signals each month, factoring seniority, location, skills, and company profile.

Match outbound to budget before clicking "reveal contact."

Layer 03

Open-to-Offers

A behavioral receptiveness signal per candidate. Built from passive patterns across multiple sources. Different from LinkedIn's "Open to Work" because the candidate doesn't have to raise their hand.

Outreach goes to people most likely to respond.

Launch an agent in two minutes.

It's as simple as this.

Pick a sample role

Pick a sample role to demo with.

Three roles, pre-loaded with anonymized candidates.

Have your own role in mind?

Sign up and run the agent on your real description.

Describe my own
Senior iOS · Q2 24 candidates · Created Apr 12
Draft
Agents / Senior iOS · sourcing Calibrating

Let's calibrate

Tell me who you are looking for — paste a job description, describe the role, or pick from past projects.

Paste JD Describe in words From past projects
  • I will extract all relevant criteria from your description
  • You will preview sample profiles before launch
  • You set the daily delivery cadence and approval rules
Describe the role you are hiring for…
↵ to send · ⌘↵ for new line
Calibration
I will show parsed parameters here as you describe the role.
Senior iOS Engineer · payments · 5+ years · NYC / SF / Remote
Skills: Swift, UIKit · Domain: payments / fintech
Daily target How many new candidates per day?
5leads
15leads
25leads
50leads
75leads
Destination Where do matched candidates go?
Manual review queue Review each match before saving
Auto-save to selected project Saves to Senior iOS · Q2 » Saved candidates
Schedule Daily at 09:00 (PT)
Frequency
Hourly
Daily
Weekly
09:00
🌐America/Los_Angeles
Mo Tu We Th Fr Sa Su
4 sample candidates from your criteria Generated by the agent. Refresh to re-source.
Looks accurate? Yes No
Sourced0/25
Approved0
Skipped0
Rejected0
Last batch

Sourcing in progress

Agent is searching for more candidates — next batch arrives in ~45 min.

Past batches
Show all ▾
Yesterday· 25 candidates · 18 approved → Saved candidates
2 days ago· 25 candidates · 15 approved → Saved candidates
Sourced today25/25
Approved8
Skipped3
Rejected1
Last batchToday, 09:14 AM

Today's batch · 25 new

Sort: Market Value ▾
Sourced today25/25
Approved8
Skipped3
Rejected1
Last batchToday, 09:14 AM

Today's batch · 25 new

Sort: Market Value ▾
SC
Sarah Chen
Staff Backend Engineer · Stripe
Open to offers SF Bay, CA
Salary
$ 295k
Experience
12 years
Key Information
Why match
AI summary · auto-generated
Experience
Matching Skills
Skills
Languages

Custom GPT agent vs. Glozo's sourcing agent.

Five things a DIY GPT agent can't do. All five are how Glozo Agent earns its match.

Custom GPT agent
Glozo's sourcing agent
Keyword overlap on the JD and the public profile
Skill Graph. Weighted skills inferred from work history, not extracted from a resume.
Salary fit is your guess
Market Value per candidate, statistical model trained on 10M+ data points per month.
Reply rate is hope
Open-to-Offers. Behavioral receptiveness signal, predicted from passive patterns, not self-reported.
Locked to one source you can scrape
Sources across 30+ public sources and your imported contacts.
Time to build, ongoing maintenance
Two minutes to launch.

Glozo is a sourcing layer. Hiring decisions stay with you.

Free to start.

Run a sourcing agent end to end without paying.
Available on every plan, free included
No card required
Searches, calibration, shortlists all included
Start free

Common questions.

What is a sourcing agent?

A sourcing agent is software that runs multi-step sourcing tasks on its own. Given a role, it finds target profiles, surfaces likely fits, and prepares a shortlist. Most agents on the market combine LLMs with public profile data and matching models.

Glozo's sourcing agent is a specific kind of this. It runs only the sourcing layer (not screening, scheduling, or auto-messaging), and the depth comes from proprietary data layers: Skill Graph, Market Value, Open-to-Offers. We don't rely on a smarter LLM prompt. The moat is the data.

Is this just a wrapper around GPT?

No. The agent runs on three proprietary data layers. Skill Graph weighs each candidate's history across 30+ public sources. Market Value prices each candidate from 10M+ market signals each month. Open-to-Offers reads behavioral patterns that suggest receptiveness.

A GPT prompt can't reproduce this. The data isn't in public APIs.

Why not build my own sourcing agent in Claude or Cursor?

You probably could, for the simple case. Claude or Cursor can write a Boolean query, hit LinkedIn or GitHub, and return a list of profiles. What's hard to reproduce is the data layer underneath.

Skill Graph requires reading 30+ sources and building weighted skill representations per candidate. That's a data engineering task, not a prompt task. Market Value requires a continuously updated compensation model trained on millions of market signals. Open-to-Offers requires behavioral pattern detection across multiple sources over time.

You can build one of these yourself in a month of focused work. We've spent years on all three. Buy the data layer, build everything else.

When should I use the agent vs fast search?

Use fast search when the brief is clear: senior backend in NYC, 7+ years, Go or Rust. The pre-indexed state returns matches in seconds.

Use the agent when the brief is fuzzy, the role is hard to source, or the obvious candidates aren't enough. The agent takes a deeper pass. It re-processes data from sources, re-weights matches against your criteria, and digs into corners a fast scan can't reach. Think of it as fast scan vs deep dive.

How long until I see results?

Minutes to hours. Simpler roles return shortlists in under an hour. Harder roles (cross-domain seniority, narrow technical niches) can take longer. The agent works in the background, so you don't sit and wait. We notify you when the run is done.

Can I see what the agent did?

Yes. Every candidate on the shortlist arrives with three visible signals: a matching summary built from the Skill Graph, a Market Value estimate, and the Open-to-Offers flag where present. You can expand any of them to see the underlying data.

The agent prepares the shortlist; you decide who to contact. Hiring decisions stay with you.

Is the agent in beta, and does it cost extra?

Yes, the agent is in beta. It's included on every Glozo plan, free tier included, at no extra cost. There's no separate paid tier planned for it.

Beta here means we're still refining edge cases, not that the product gets paywalled later. Today and after: searches, calibration, shortlists, all free.

Can my own agents (Claude, Cursor) call Glozo's sourcing agent?

Yes, today. Glozo runs in browser-based AI tools (Claude, Cursor, Cowork via the Chrome integration). Grant the tab access and your agent can call the Glozo sourcing agent through the UI as part of its own flow.

A dedicated MCP server, exposing Glozo's sourcing agent as a native tool any agent can call directly, ships next.

Launch your first agent.

Two minutes. Free to start. Included on every plan.