Mantiks review: what it does, what it costs, and where the data stops

Mantiks sells a simple idea: a job posting is a buying signal. A company hiring three SDRs needs sales tooling, a company hiring its first data engineer needs a data stack, and whoever posted the role knows exactly which budget it comes from. The Mantiks pitch - “track opportunities from job postings” - is to watch the boards for you, flag the companies that just started hiring for the roles you care about, and hand you the decision-maker’s email, phone and LinkedIn so you can act on the signal before a competitor does.

That puts Mantiks in the same family as the hiring-signals tools built on job-postings data, but with a distinct centre of gravity: the contact layer. This review covers what the platform actually includes, the rate card as advertised in August 2026, the developer APIs it sells, and the point where a prospecting tool stops being the right shape and a raw jobs API takes over.

What Mantiks sells

The platform is built for outbound teams - sales, recruiting agencies, consultancies - and the features map onto that audience directly:

• Opportunity detection. Saved searches over new job postings with unlimited alerts, so a company matching your criteria surfaces the day it starts hiring.
• Contact identification. For each opportunity, Mantiks names the likely decision-makers and reveals email, phone and LinkedIn profile. Reveals are metered in credits; previewing jobs and contacts is unlimited.
• CV matching. The recruiter-side trick: import a candidate’s CV and get back the list of companies currently recruiting similar profiles.
• Agency unmasking. A feature that tries to reveal the end client behind a recruitment agency’s anonymised posting.
• Delivery. AI monitoring with custom instructions, plus feeds into a CRM or ATS through native integrations, an API and webhooks on the higher tier.

Coverage runs through four job boards: LinkedIn, Indeed, Glassdoor and Welcome to the Jungle, with data refreshed every 24 hours and, per the API marketing, several years of recruitment history behind it. The company claims more than 1,000 customers.

The pricing

Prices are public and quoted in euros. Both self-serve tiers are billed monthly but carry a 12-month commitment:

Two line items deserve attention before you sign. First, the commitment: the advertised monthly prices are annual-contract prices, so the real decision is €1,188 or €2,280 a year, not a month-to-month experiment - budget the 7-day trial accordingly. Second, the meter: on the platform, credits burn on contact reveals; on the API, Mantiks charges one credit per company found, regardless of how many postings that company has. That metering is genuinely favourable if you want accounts, and irrelevant if you want postings. Paid onboarding (from €790) and sales training (from €250) sit alongside, which tells you the intended buyer is a sales team, not a lone developer.

The developer surface: two different APIs

Mantiks has a real API, and it is shaped like the product. The main endpoint, GET api.mantiks.io/company/search, takes a boolean query over job titles and descriptions plus company filters - and returns results aggregated by company. A second endpoint, GET api.mantiks.io/company/jobs, tracks the recruitment activity of companies you name and attaches the hiring-manager contacts. Twenty-plus fields per job, refreshed every 24 hours, 50 free credits to test with. The unit of retrieval is the account, because the product is prospecting.

Separately, Mantiks publishes per-board scraping APIs on RapidAPI - one each for LinkedIn, Indeed, Glassdoor and Welcome to the Jungle - with a free tier of 25 requests a month and a 1,000-requests-an-hour ceiling. These return board-shaped data: each API mirrors its board’s own fields, so a Glassdoor record and a LinkedIn record arrive in different schemas, and stitching four boards into one deduplicated view of the market is your problem. That is the classic per-board scraper trade-off, and it is the main reason unified jobs APIs exist.

Where Mantiks stops

None of this is a criticism of what Mantiks is - it is a well-aimed prospecting tool. But three boundaries matter if you are evaluating it as a data source:

• Four boards is not the market. There is no ATS-direct coverage - no Workday, Greenhouse, Lever, Ashby, Workable or SmartRecruiters feeds - so postings that never hit the four boards never enter the dataset, and board postings arrive on the boards’ own delay.
• The shape is accounts, not postings. Aggregation by company is exactly right for lead lists and exactly wrong for job-level work: salary analysis, skills demand, feeding a job board, training a matching model.
• The meter is built for reveals. 500 credits a month prices a steady outbound motion. It does not price pulling tens of thousands of postings for analysis - that workload exhausts any per-company or per-contact meter by design.

If the signal is enough, and the data is the point

The honest way to decide: if your team’s bottleneck is who to call this week, Mantiks earns its €99 - the contact layer is the product, and building reliable email and phone reveal yourself is a bad use of an engineering quarter.

If your bottleneck is the underlying data, the economics invert. A raw jobs API meters postings, not reveals. JobsPipe’s index currently holds 3.38 million live postings from more than 600,000 distinct companies, collected from the boards and the ATS layer - LinkedIn, Indeed, Workday, Greenhouse, Lever, Ashby, Workable, SmartRecruiters and more - deduplicated into one schema. The same hiring-need query a Mantiks saved search runs looks like this:

curl https://api.jobspipe.dev/v1/jobs/search \
  -H "Authorization: Bearer jp_live_your_key_here" \
  -H "Content-Type: application/json" \
  -d '{ "skills_or": ["snowflake", "dbt"], "job_country_code_or": ["US"], "posted_at_max_age_days": 7, "limit": 25 }'

Every result carries the posting itself - normalized title, company, location, parsed compensation, occupation_code and skills - so the same call powers prospecting, analytics or a product feature. For the standing-alert use case, Signals watches a search server-side and tells you when a company starts hiring, which is the Mantiks trigger without the per-contact meter. And if you are pricing this against other data vendors, the Coresignal rate card makes a useful third point of comparison: per-record credits again, just metered on records instead of reveals.

The free tier is 1,000 jobs a month - against 25 requests a month on the per-board RapidAPI free tier - on a wider source base, with no annual commitment. Run the same search both ways during a Mantiks trial week and you will know within an hour which shape your use case actually needs.