Recruitment · head to head
Manatal vs SeekOut

Manatal
Recruitment
Low-cost applicant tracking and recruitment CRM with candidate enrichment, sold to both in-house teams and agencies
- From
- On request
- Rated
- -

SeekOut
Recruitment
AI candidate search across a claimed billion-plus profile database, with a published self-serve price
- From
- On request
- Rated
- -
The short version
- Each has a real cost: Manatal pricing is per recruiter seat, so putting every hiring manager into the system to review candidates multiplies the licence count and erases the price advantage.; SeekOut the self-serve Recruit Core tier caps monthly contacts at 500 and exports at 1,000, which an active recruiter can exhaust well before the month ends
- They diverge on capability: Manatal covers Candidate enrichment, SeekOut covers Candidate database search.
- Prices and features above were last checked on 1 September 2026.
Where they differ
Only the attributes on which Manatal and SeekOut actually diverge.
Identical on both: starting price (On request), free tier (No), user rating (Not yet rated), category (Recruitment).
What each one covers
Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.
Only in Manatal
- Candidate enrichment
- AI candidate scoring
- Recruitment CRM
- Multi-board posting
- CV parsing
- Careers page builder
- Custom pipelines
- Reporting
Only in SeekOut
- Candidate database search
- Outreach sequencing
- Talent rediscovery
- Market intelligence
- SeekOut Spot
What people use each for
The jobs each tool is most often brought in to do.
Manatal
- A small recruitment agency that needs client, candidate and placement tracking without an enterprise contractnot SeekOut
- An in-house team in Asia Pacific that wants candidate enrichment without paying enterprise ATS pricesnot SeekOut
- A company processing high applicant volume that needs automated ranking to triage a shortlistnot SeekOut
- A recruiter running both contingent search and internal hiring from one databasenot SeekOut
SeekOut
- An individual recruiter or small agency wanting to start sourcing immediately on a card without a sales callnot Manatal
- A talent acquisition team that has outgrown a self-serve seat cap and needs ATS-integrated sourcing across the teamnot Manatal
- An employer benchmarking compensation and talent pool size for a hard-to-fill role before opening a searchnot Manatal
- A company wanting to try an AI-assisted sourcing service billed per role, as an alternative to paying a recruiting agency percentage feenot Manatal
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Manatal
- Pricing is per recruiter seat, so putting every hiring manager into the system to review candidates multiplies the licence count and erases the price advantage.
- Candidate enrichment depends on public profile data, so accuracy drops sharply in markets where professional networking sites have low penetration and the scores become misleading rather than useful.
- Integrations with major HRIS and payroll systems are limited compared with Western competitors, so new hire handover is frequently a CSV export rather than a sync.
- Support operates on Indochina business hours, which leaves European afternoons and all of North American working hours outside the responsive window.
- Reporting covers recruiter activity and source data but lacks the cohort and quality-of-hire analysis a mature talent function expects, and custom analysis means exporting to a spreadsheet.
SeekOut
- The self-serve Recruit Core tier caps monthly contacts at 500 and exports at 1,000, which an active recruiter can exhaust well before the month ends
- Moving from Recruit Core to team-level plans reverts to custom quoting, so the published entry price does not scale predictably as a team grows
- Candidate data is aggregated from public and licensed sources, so contact accuracy and freshness vary by role type and can lag for less public roles
- ATS integration and market intelligence, the features larger teams actually need, sit behind the quoted tiers rather than the published price
- SeekOut Spot's per-role pricing model still requires a sales conversation to size, despite being marketed as a lower-cost alternative to agencies
- A large claimed database size does not guarantee coverage in every geography or niche technical skill, and buyers cannot verify coverage for their specific roles before purchase
Pricing, plan by plan
Manatal
On request- Professional$undefined/month
- Per recruiter seat
- Unlimited jobs and candidates
- Candidate enrichment and AI scoring
- Enterprise$undefined/month
- Per recruiter seat at a higher rate
- Custom fields and advanced permissions
- Recruitment CRM for agency use
- Custom$undefined/year
- Negotiated terms for larger teams
- Single sign-on and security review
- Dedicated account management
SeekOut
On request- Recruit Core$149/month
- Unlimited searches
- 500 monthly contacts
- 1,000 exports/month
- Recruit Sourcing / Full Funnel$undefined/year
- ATS integration
- Talent rediscovery
- Market intelligence
Which should you pick?
Choose SeekOut if
- You need candidate database search.
- You work on Web, Chrome Extension.
- You also want outreach sequencing.
Questions people ask
- Is Manatal or SeekOut better?
- Neither clearly leads. Manatal starts at On request and SeekOut at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Manatal or SeekOut?
- Manatal starts at On request and SeekOut at On request.
- Does Manatal or SeekOut run on more platforms?
- Manatal runs on Web. SeekOut runs on Web, Chrome Extension.
- What is Manatal best used for?
- Manatal is most often used for a small recruitment agency that needs client, candidate and placement tracking without an enterprise contract, an in-house team in asia pacific that wants candidate enrichment without paying enterprise ats prices, a company processing high applicant volume that needs automated ranking to triage a shortlist, a recruiter running both contingent search and internal hiring from one database. Of those, a small recruitment agency that needs client, candidate and placement tracking without an enterprise contract and an in-house team in asia pacific that wants candidate enrichment without paying enterprise ats prices are not what SeekOut is typically brought in for.
- What can Manatal do that SeekOut cannot?
- Manatal covers Candidate enrichment, AI candidate scoring, Recruitment CRM, Multi-board posting. SeekOut covers Candidate database search, Outreach sequencing, Talent rediscovery, Market intelligence.
Answered from the vendors’ own pages
Manatal: Is it for agencies or in-house teams?
Both. The agency mode adds client and placement management; the corporate mode is a conventional ATS. Buying the wrong mode means paying for modules you never open.
SeekOut: Is there a genuinely self-serve price?
Yes, Recruit Core is $149/month billed annually or $179/month billed monthly, purchasable without a sales call, with a 14-day free trial.
Manatal: How is it priced compared with other ATS products?
Per recruiter seat per month. That is not comparable with vendors that charge per active job slot or per employee, so model your real user count before comparing headline numbers.
SeekOut: What happens when I hit the monthly contact limit?
Recruit Core caps at 500 monthly contacts and 1,000 exports; exceeding that requires upgrading to a quoted team tier.
Manatal: Where is candidate data hosted?
On cloud infrastructure with GDPR commitments, but region-specific residency guarantees are weaker than EU-native vendors offer, which matters for regulated European buyers.
SeekOut: Is SeekOut Spot the same product as Recruit?
No, Spot is a separate AI-assisted, human-reviewed sourcing service billed per role or per contractor rather than a seat-based search tool.
Manatal: Does the AI scoring actually work?
It ranks reliably against structured requirements such as skills and experience length. It is far less reliable where enrichment data is sparse.
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