Ask r/recruiting what they think of AI sourcing agents and the top answer is some version of "they're just ChatGPT with a nicer login page." Half the market has earned that insult. The other half is quietly doing real work: running searches overnight, drafting outreach that references a candidate's actual history, and filling Monday-morning shortlists while the recruiter sleeps.
The problem is telling the halves apart from a demo. HR.com's Future of Recruitment Technologies study puts the gap in numbers: 13% of HR professionals actively use AI agents for recruiting while 50% are still exploring, which means most buyers right now are comparing marketing pages, not products.
This guide is the comparison. Ten sourcing agents, the prices vendors bury behind "book a demo," and a plain answer on who each one is for. One scope note before we start: this is about sourcing job candidates. If you searched "sourcing agent" and you're looking for someone to find factory suppliers in Shenzhen, this is the wrong article.
What counts as an agent here
An AI sourcing agent is software that pursues a sourcing goal across multiple steps on its own: it takes a role, finds matching candidates, and moves work forward without a human prompting every action. Everything in the table below clears that bar, or is flagged where it doesn't.
That definition is doing a lot of work, because the label got applied to every search box with a chat window the moment "agent" started selling. If you are about to sit through demos and want the questions that separate the two, we wrote the full framework separately: how to tell a real AI sourcing agent from a tool with a chatbot bolted on sets out five questions to put to any vendor, including us, and what a dodge on each one tells you. This page assumes you have already made that cut and want to know which products to shortlist.
Ten agents at a glance
Prices verified July 2026, on vendor pricing pages where they exist and marked "custom" where they don't. Database sizes are vendor-reported throughout; nobody audits these numbers.
| Agent | Agent test | Runs on | Pricing | Best for |
|---|---|---|---|---|
| LinkedIn Hiring Assistant | Pass | LinkedIn's own network (1B+ members, vendor-reported) | Add-on to Recruiter seats; price undisclosed | Teams already living in LinkedIn Recruiter |
| Juicebox Agents | Pass | PeopleGPT search, 800M+ profiles (vendor-reported) | $199/agent/mo on top of a $99-179/seat/mo annual plan ($119-199 monthly), read 7 Sep 2026 | Small teams wanting always-on outbound |
| Gem AI Sourcing Agent | Pass | Gem platform data, 800M+ profiles (vendor-reported) | Custom | Teams on Gem's all-in-one platform |
| Glozo Sourcing Agent | Pass (gated by design) | Glozo index from 30+ sources, plus Skill Graph, Market Value, Open to Offers signals | Free | Recruiters who want signal-driven background sourcing without new spend |
| hireEZ agentic AI | Partial: platform workflows | hireEZ sourcing database | On top of seat pricing; the published solo seat is $494/mo, team pricing quoted, read 7 Sep 2026 | Existing hireEZ customers |
| Metaview sourcing agent | Pass (vendor-claimed autonomy) | Own index plus your JDs, notes, past candidates | Free to start; paid plans on request | Teams already using Metaview interview notes |
| Pin | Pass | 850M+ profiles via data partners (vendor-reported) | $99-249/user/mo (annual billing), agents included | Solo recruiters and agencies wanting one predictable price |
| SeekOut agentic sourcing | Partial: assistive, not autonomous | SeekOut index, 1B+ profiles (vendor-reported) | Included in Recruit; the self-serve Core seat is $149/mo on annual billing, read 7 Sep 2026 | Teams already on SeekOut Recruit |
| SeekOut Spot | Withdrawn | — | No longer sold. As of 7 Sep 2026 Spot appears nowhere on SeekOut's site and its URLs 404; SeekOut's nav lists only Recruit, Sam and MCP | — |
| Fetcher | Partial: batch automation | Own sourcing database | On request | Steady-drip candidate batches per role |
| Tezi Max | Pass (early-stage) | Own stack, end-to-end | Custom, pilot pricing | Startups hiring many roles at once, comfortable being early |
Also in the market: GoPerfect, Moonhub, Beam, Braintrust Nexus, and the agent layers inside enterprise suites (Eightfold, iCIMS Coalesce, SmartRecruiters' Winston). We cut them for scope, not for quality: this list stays with agents a recruiter or a small team can actually evaluate and buy this quarter.
The ten, one by one
LinkedIn Hiring Assistant
The incumbent's answer, and both competitor roundups we studied somehow leave it out. Hiring Assistant went generally available in September 2025 and got a meaningful update in February 2026: Microsoft Teams collaboration, AI follow-ups, and applicant targeting. It sources within LinkedIn's network, drafts InMails, handles follow-ups, and hands you a reviewed pipeline. LinkedIn's own numbers say users review 62% fewer profiles per hire and see 69% higher InMail acceptance; treat those as marketing until an independent source repeats them.
Two real constraints. It only sees LinkedIn, so the quarter of the talent market that lives on GitHub, conference rosters, and everywhere else stays invisible. And it requires a Recruiter license, which starts near $1,680 a year for Lite and runs $10,800 to $15,000 per Corporate seat, with the Hiring Assistant add-on price still undisclosed. Our LinkedIn Recruiter cost breakdown covers what that stack really costs. If your whole workflow already lives in Recruiter, this is the lowest-friction agent on the list. If you're not already paying for Recruiter, it's the most expensive.
Juicebox Agents
The most transparent pricing in the category: $199 per agent per month, stacked on a per-seat plan that is $99 (Starter) or $179 (Growth) on annual billing, $119 or $199 month to month. A single recruiter running one agent lands around $298 to $378 a year-billed, $318 to $398 monthly, which is worth computing before the demo because no one will compute it for you. One caution on reading Juicebox's page: it loads on the annual view and the billing toggle does not clearly show which mode is selected, which is why third-party figures for it disagree by $20 to $40. The agent runs continuously in the background on top of Juicebox's PeopleGPT natural-language search and its 800M-profile index, and you can set it to auto-shortlist or auto-email, with unlimited contact credits inside the agent.
The honest read: Juicebox is a strong search layer with a genuinely always-on agent bolted where it belongs. The caveat is that everything downstream of sourcing and first-touch email still happens elsewhere, and the per-seat plus per-agent math grows quickly for teams. For a solo recruiter who wants outbound running overnight, it's one of the two or three obvious candidates to trial. We took apart every tier, credit cap, and gotcha in our Juicebox pricing breakdown.
Gem AI Sourcing Agent
Gem's agent sources around the clock across its 800M-profile index and personalizes outreach per candidate across email, InMail, and SMS, with automated follow-ups. It's part of Gem's pitch as an AI-first all-in-one platform (ATS, CRM, sourcing, scheduling), and that's exactly who it's for: if Gem is your system of record, the agent inherits your full funnel context, which genuinely improves targeting.
Pricing is custom, a startups plan exists, and public numbers don't. Gem is also building GeMCP, a Model Context Protocol layer it previewed in June 2026, which signals where the platform is headed: your assistant talking to Gem's data directly. Strong choice for Gem shops; hard to justify buying the whole platform just to get the agent.
Glozo Sourcing Agent
Ours, so hold us to the same test. The agent is created from a search: run a search in Glozo, hand it to the agent, and it keeps working the brief in the background, emailing you when new results are worth your time. It passes the data question with the three signals the rest of this list doesn't carry: a match rationale built from the Skill Graph (reasoning you can repeat to a hiring manager, not a percentage), a Market Value estimate from a model trained on 10M+ monthly data points (so you know who fits the budget before spending outreach credits), and an Open to Offers signal that predicts receptiveness instead of waiting for a candidate to flip a badge.
The honest caveat: it runs in manual mode today. It sources and surfaces continuously; you review the digest and decide who gets contacted. It will not auto-send outreach on your behalf, and the deeper autonomy tier is still in development. If your definition of agent requires auto-send, that's a gate we've deliberately kept closed for now. It's also free, which makes it the cheapest way on this list to find out whether background sourcing changes your week. The Sourcing Agent page covers how it compares to building your own GPT wrapper.
hireEZ agentic AI
hireEZ added agent workflows across its existing outbound platform: sourcing, matching, engagement, scheduling. It's a "partial" on our test not because the technology is thin but because it's packaged as workflows inside a seat-priced platform rather than a self-directed agent you point at a goal. Existing hireEZ customers should turn it on and will likely keep it. Buying into the platform for the agent alone is a bigger decision, and pricing is custom on top of seats, so model the full-year number before committing.
Metaview sourcing agent
Metaview built its name on AI interview notes and moved into sourcing with an agent it markets as "truly autonomous." The interesting part of the pitch is input flexibility: it reads JDs, resumes, past candidates, or a plain-English description and searches from that context rather than rigid filters. Autonomy claims are vendor language until you test them, and the sourcing product is young next to its notes product. The natural fit is teams already on Metaview for interviews, where the agent inherits real role context from actual conversations. There's a free way in, with paid plans on request.
Pin
Pin includes its agents in every plan rather than selling them as an add-on: $99 a month solo, $149 professional, $249 business on annual billing, running on a partner-fed index of 850M+ profiles, with outreach sequences across email, LinkedIn, and SMS. That flat, published pricing is genuinely rare in this market and worth crediting.
Two things to know. Pin's marketing leans on internal numbers (5x response rates, an "83% acceptance" figure) that come with no sample size or methodology, so ignore them and run your own two-week trial instead; the free tier makes that easy. And Pin is a young company shipping fast, which cuts both ways: quick feature velocity, short track record. For solo recruiters and small agencies comparing it against Juicebox, the difference is packaging: Pin bundles agents into one price, Juicebox itemizes them.
SeekOut agentic sourcing, and what happened to Spot
SeekOut's agent work sits inside Recruit rather than beside it. The assistive layer drafts searches, expands a shortlist and writes outreach, but it will not run a role end to end without you, which is why it scores Partial here. That is a reasonable deal if you already pay for the index — the self-serve Core seat is $149 a month on annual billing, and we break the tiers down in our SeekOut pricing guide — and a weak reason to buy in if you do not.
SeekOut appears twice in the table because the second entry is gone. SeekOut Spot was the done-for-you side, where you bought delivered candidates rather than software. As of 7 September 2026 it appears nowhere on SeekOut's site, every Spot URL returns a 404, and the navigation lists only Recruit, Sam and MCP. SeekOut has published no statement, so treat Spot as withdrawn from sale rather than formally discontinued, and re-confirm any Spot quote you were given earlier this year before you budget against it.
Fetcher
The veteran. Fetcher was automating passive-candidate sourcing before "agent" was a category, and its model is still the steady drip: batches of vetted candidates per role, on a schedule, with outreach automation attached. We mark it "partial" because it predates the goal-driven, reasoning-loop pattern the newer agents use; it automates a pipeline rather than pursuing a brief. That's not an insult. For predictable, ongoing roles where you want twenty decent candidates every Tuesday, boring reliability beats agentic ambition. Pricing is on request.
Tezi Max
The category's frontier bet: Max aims to run recruiting end-to-end, from sourcing through screening to scheduling, as close to autonomously as anyone currently claims. Early pilots have priced per role or per hire rather than per seat, which tells you how early this is. The trade is obvious: highest ceiling on the list, shortest track record, and pilot-stage pricing you'll negotiate rather than read off a page. Series B-D startups with a dozen simultaneous roles and appetite for being a design partner are the natural fit. Everyone else should watch it for a year.
Judge agents by what they decide with, not how many profiles they search
Every vendor page in this category leads with a database number: 800 million, 850 million, a billion. After the first few hundred million, the number stops mattering. The candidates you want appear in every major index. What differs is what the agent knows when it decides who to surface and what to write.
Three questions expose the difference in any demo. Can the agent explain why this candidate matches, in terms you could repeat to a hiring manager, or does it hand you a list ordered by keyword overlap? Does it know what the candidate likely costs, so the shortlist fits the budget before you've burned a week of outreach on people your client can't afford? And does it know who is likely to respond, or will it spend your sender reputation on candidates who haven't considered a move since 2022?
Most agents on this list answer one of the three, usually the first, thinly. This is the axis where Glozo's sourcing stack concentrates its effort: match rationale, Market Value, and Open to Offers travel with every candidate the agent surfaces, before any credits are spent. Whichever tool you pick, ask the three questions in the demo. The vendors that can't answer them will change the subject to database size.
Agents vs. MCP-connected assistants: the 2026 question nobody's roundup covers
There's a new option this year that muddies the category. Your existing AI assistant (Claude, ChatGPT, Copilot) can now connect directly to recruiting tools through MCP servers, and suddenly "do I need a sourcing agent?" has a second answer. We published a full guide to MCP for recruiters this month; the decision line runs like this.
An MCP-connected assistant is enough when the work is on-demand: query your ATS in plain English, pull a weekly pipeline report, draft re-engagement emails from your own database. You prompt, it acts, it stops. It's the cheapest path because you already pay for the assistant, and guides like our Claude for recruiters workflows show how far that goes.
A purpose-built agent earns its keep when the work is continuous and the data is proprietary. An assistant with MCP access to your ATS still only sees your ATS. It has no external candidate index, no compensation model, no receptiveness signal, and it stops working when you close the laptop. Background sourcing on signals your stack doesn't carry is exactly the job the agents in this list exist for. Most teams will end up with both: an assistant wired into their tools for the on-demand work, an agent for the always-on hunt.
Two things deliberately left out of the table
Both come up in every conversation about this category, and neither is a commercial sourcing agent, which is why they are not in the ten.
Self-hosted agents. OpenClaw is the one recruiters actually ask about. It is an open-source agent you run yourself, so there is no seat price to compare, no vendor index behind it, and no support number when a run fails at 3am. What you get instead is control: your own infrastructure, your own data boundaries, and no per-credit meter. It belongs in a different comparison from the ten above, because the question it answers is "can my team operate this" rather than "is this worth the subscription." We have written it up on its own terms, alongside OpenClaw versus the Hermes agent.
Custom GPTs you build yourself. Cheaper than everything in the table and genuinely useful for drafting and triage, but the ceiling is hard and it is not an intelligence ceiling. A custom GPT can only work on data you hand it, which means it inherits every blind spot in your existing sourcing. That is the whole argument, and we made it at length in why a custom GPT can't source candidates.
The compliance corner
Automated hiring tools now sit inside real regulation in several US jurisdictions, and an agent that sources and contacts candidates is the low-risk end of the spectrum, while anything that filters or influences hiring decisions carries disclosure duties. Current state of play:
| Jurisdiction | Rule | What it means for agent use |
|---|---|---|
| New York City | Local Law 144 (in force) | Automated tools used in hiring decisions need annual bias audits and candidate notice. Outbound sourcing is outside the core scope; screening is inside it. |
| Illinois | AI amendments to the Human Rights Act (in force 2026) | Employers using AI in employment decisions must avoid discriminatory effect and provide notice. |
| California | Automated-decision system rules under FEHA (in force) | AI tools in hiring fall under anti-discrimination rules; keep records of what the tool decided and why. |
| Colorado | Colorado AI Act (delayed to 2027) | Not yet in force. High-risk AI duties arrive in 2027; worth tracking if you hire there. |
The practical rule for sourcing agents: proactive outreach to candidates is the safe zone, because the candidate decides whether to engage and no employment decision is being automated. The moment agent output starts feeding interview or hiring decisions, you're in disclosure territory, and you should know which jurisdiction's rules apply before the tool does it, not after. Ask every vendor which side of that line their defaults sit on.
How to choose from here
Budget sorts the list fast, and the bands moved this year. At zero incremental dollars you are testing Glozo's agent, Pin's free tier, or Metaview's free entry point. Under $250 a month now covers Pin, Juicebox and SeekOut's self-serve Recruit Core seat at $149, which was a five-figure conversation until SeekOut published that tier. Above $250 you are buying platforms: hireEZ's published solo seat is $494 and its team pricing is quoted, Gem is a custom FTE-based quote, and LinkedIn is a seat you may already own. At that point the agent question becomes a platform question.
Then run the fit checks: which index actually covers your roles, whether the agent respects your existing stack or wants to replace it, and where the human gates sit. We keep a full set of demo questions in how to choose an AI sourcing agent, and if you're still deciding whether an agent is even the right category, the AI recruiting tools buyer's guide maps all five tool categories with pricing.
One closing habit separates good buyers from sorry ones in this market: date everything. This list was accurate in July 2026. Two of its entries didn't exist as products a year ago, one incumbent's add-on price is still secret, and at least one vendor will reprice before Christmas. Verify, trial on a real role, and keep the receipts.