Most hiring tools forget everything between roles.
Recruiters do the same work twice because the context never compounds. The next role starts from an empty folder, not from what you already learned.
Strong candidates disappear
People you already screened sit in old inboxes and dead spreadsheets. The next time a fitting role opens, nobody remembers them.
Decisions leave no trace
Why someone was rejected, what the manager really wanted, which question exposed the risk: it lives in calls and comments, then it is gone.
Every search starts from zero
A classic ATS stores applications. It does not learn. So each new role repeats the same reading, ranking, and guessing from scratch.
Three products, one engine that learns.
sHRark Core scores, explains, and remembers. The same core powers sHRark ATS for your own hiring and sHRark Jobs for matching against our curated pool. We adapt one working engine, we do not rebuild it per product.
sHRark Core
Scoring · evidence · memory
sHRark ATS
For teams hiring on their own data
sHRark Jobs
For companies that need people now
sHRark Core
For new matching use cases
sHRark ATS
For teams hiring on their own data
Your own candidate history is going to waste.
Score and rank your own candidates for your own roles, with the evidence behind every decision and memory that improves the next one.
See sHRark ATSsHRark Jobs
For companies that need people now
Sourcing is slow and the shortlist is shallow.
Post a role and the same engine returns a short, anonymized shortlist from our curated pool, each match with the reasoning behind it.
See sHRark JobssHRark Core
For new matching use cases
Matching and fit checks get rebuilt everywhere.
The scoring, explanation, and memory engine is domain neutral. New applications come from configuration, not a rewrite from scratch.
Talk about CoreYour candidate history, turned into a ranked shortlist with evidence.
Create a role, upload CVs or LinkedIn PDFs, and sHRark ranks every eligible candidate, shows the evidence, flags the risks, and suggests the questions to ask. Then it learns from what you decide.
Ranking you can defend
Every score links back to source text, so you can explain a shortlist to a hiring manager in seconds, not justify a black box.
Risks and questions surfaced
sHRark names the gaps and hands you the exact questions to test them in the interview, instead of leaving you to find them later.
Memory that compounds
Notes, stage moves, rejections, and hires feed the next ranking, so the system gets better at how your team specifically hires.
Candidate A.K.
Role: Senior Product Manager
Match score
Strengths
- 8 years leading product teams
- Shipped 3 products from idea to launch
Risk to test
- No experience in a regulated industry
Evidence
“Led the team that rebuilt checkout and cut failed payments by a third.”
Suggested question
Tell me about a launch that slipped, and how you brought it back on track.
A two-sided match, run by the same engine.
Employers describe the role. Experienced candidates submit once. sHRark keeps the pool verified, ranks anonymized fit, and introduces only the strongest matches with the reasoning behind them.
Tell us the role, get a reasoned shortlist.
Skip the sourcing grind. The same engine that powers sHRark ATS ranks our curated pool and returns a short, anonymized shortlist of the strongest matches.
- Anonymized shortlist, not a CV dump
- Every match comes with its reasoning
- You only see people who actually fit
Put your CV where serious roles can find it.
Submit your CV once. If your experience fits an open role, employers first see an anonymized profile built around evidence, rates, availability, and what to verify in conversation.
- Every CV is reviewed by a person, by design
- Once in, you manage everything from a private link
- Update or withdraw whenever you want
We keep the pool small and verified. Candidates are added only after a personal review, never by a public scrape.
AI memory that compounds after every role.
sHRark is not another place to store applicants. It turns candidate data, role context, notes, decisions, and outcomes into reusable ranking signal.
Cross-role and cross-client memory
Upload a candidate once. sHRark can rank them against every eligible role, and in agency work across clients when the data scope allows it.
Full feedback loop
Recruiter notes, manager feedback, stage moves, rejections, and hires change future rankings. Job-ad lessons also feed the next search.
Auditable AI scoring
Azure OpenAI GPT-5.4 produces the base score, then deterministic guards, evidence links, and score history explain why the number changed.
Share sHRark when it helps. Your trial can grow with you.
The product value still comes first: ranking, memory, and feedback. Referrals are a practical bonus for teams that bring another company on board.
Recommend sHRark to another company
When a referred company is approved, your workspace receives 14 extra trial days.
The reward is applied after approval, not just after a form submit.
Earn from companies that stay
When the program opens, if a referred company moves to a paid plan, you can receive 10% of their monthly plan value as account credit or payout.
Program terms will define eligibility, payout method, and limits.
Referral rewards apply to separate companies, not same-workspace team invites.
Plans that scale with your hiring, not your headcount.
Every plan includes the full ranking engine, evidence checks, and public application links. Limits are monthly consumption: recruitment activations and parsed CVs.
Starter
€59
per month
For a single hiring stream.
- 2 recruitment activations / month
- 100 parsed CVs / month
- Ranking, evidence, public links
Team
Most popular€149
per month
For teams hiring continuously.
- 7 recruitment activations / month
- 400 parsed CVs / month
- Clients, decisions workspace, PDF exports
Business
€349
per month
For high-volume recruitment.
- 20 recruitment activations / month
- 1200 parsed CVs / month
- Full analytics, audit exports
Scale
from €790
per month
Custom volume, SSO, onboarding.
- Custom limits
- SSO and security review
- Dedicated onboarding
Start your 30-day trial on your existing candidate history.
Create a role, upload up to 50 CVs or LinkedIn profile PDFs, and test the AI memory loop on real recruiting work. After 30 days you decide whether it belongs in your process.
Your first AI ranking
Create a role, upload candidates, and get a ranking with evidence, risks, and suggested questions.
Learning from decisions
Feedback, notes, stage moves, and outcomes update future rankings instead of dying in comments.
Reusable recruiting memory
The next search starts with patterns from the previous one, including job-ad signals and cross-role fits.
Request trial access
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