AI and automation for hiring and HR, built so people still decide
Hiring and HR run on repetitive work: reading the same fields off hundreds of CVs, chasing interview times, answering the same policy question forty ways, moving a new hire's details between six systems. That is exactly what automation is good at, and exactly where AI helps most. But it is also work about people, so the rules are different here. Roiwerk builds HR and recruiting automation that clears the busywork and keeps a human on every decision that touches someone's job. It runs in your accounts, you own it, and we will tell you plainly where not to hand a choice to a machine.
Where AI belongs in HR, and where it does not
The honest split is simple. AI and automation are excellent at the preparation around a hiring or HR decision: gathering information, organising it, drafting first versions, moving data between systems, and answering questions that already have a documented answer. They are not the right tool for making the decision itself when that decision changes someone's livelihood. A model should never auto-reject a candidate, decide who gets promoted, or close a grievance. Those calls stay with your people.
So we draw the line on purpose. We automate the hours your recruiters and HR team lose to coordination and copy-paste, and we surface clean, well-organised information so the humans making the call can make it faster and with better context. The result is a team that spends its judgement where judgement matters, not on scheduling ping-pong and data entry. That framing is not a disclaimer we bolt on at the end; it shapes how every workflow in this hub is built.
- Automate the preparation: gathering, organising, drafting, and moving data
- Keep humans on every decision that affects someone's employment
- Never auto-reject candidates; AI ranks and summarises, people decide
- Surface clean information so decisions are faster, not outsourced
The bias problem, taken seriously
Recruiting AI has a real and documented failure mode: a model trained on past hiring can learn and amplify the biases in that history, quietly disadvantaging people it should not. We will not pretend that risk away, and we will not sell you a black-box scorer that rejects applicants for reasons no one can explain. That is both wrong and, in most of Europe, a legal exposure you do not want.
Our approach is deliberately narrow. AI helps read and structure applications against the job's actual requirements, and it explains what it found so a recruiter can check it. It does not assign a secret fitness score and hide the reasoning. Wherever a screening or ranking step exists, a person reviews it, the criteria are written down, and the output is auditable. If a use case cannot be built without letting a model make the final human call, we tell you not to build it.
- AI structures applications against stated job requirements, transparently
- Every ranking is explainable and reviewed by a person before it matters
- Criteria are documented, so decisions can be defended and audited
- We flag use cases that cannot be built ethically, and decline them
Built on your stack, wired to your ATS and HRIS
HR and recruiting automation is only useful if it touches the systems you actually run: your applicant tracking system, your HRIS, your calendars, your inbox, your document storage. We build on n8n, Make, and Zapier, add code and LLMs where they earn their place, and connect all of it through the APIs your tools already expose. Where an ATS has no clean API, we find another seam rather than telling you it is impossible.
Nothing runs on a platform we hold over you. Workflows live in your accounts, credentials stay yours, and the whole build is documented so your HR ops person can read and adjust it. When we hand over, you own the automations, the code, and the logic, and you can change partners or bring it in-house without losing anything. We would rather ship you an asset you control than rent you a dependency you cannot switch off.
Deep dives on each workflow, from screening and scheduling to onboarding and an HR helpdesk, so you can see exactly what we automate and where a human stays in the loop.
Will AI make hiring decisions for us?+
No, and we will not build it that way. AI reads, organises, and summarises applications against the requirements you set, and it explains what it found. A recruiter or hiring manager makes every call that affects a candidate. Nothing auto-rejects people. The point is to give your people cleaner information faster, not to hand them a verdict from a machine.
How do you handle bias in recruiting automation?+
By keeping AI narrow and transparent. It structures applications against stated job requirements and explains its reasoning, rather than assigning a hidden fitness score. Every ranking is reviewed by a person, the criteria are documented, and the output is auditable. Where a use case cannot be built without a model making the final human call, we tell you not to build it.
Does this work with our applicant tracking system and HRIS?+
Almost always. We connect through the APIs your ATS and HRIS already expose, and where a clean API is missing we find another way in. Everything runs in your accounts, wired to your calendars, inbox, and document storage, so the automation fits the tools your team already uses rather than replacing them.
Is candidate and employee data safe with this?+
It stays in systems you control. We lean toward self-hosted automation and run everything in your own accounts, which matters under the GDPR when you are handling applicant and employee data. Access is scoped, actions are logged, and we design each workflow to hold only the data it needs for the job it does.
Not sure which applies to you?
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