Hire faster, and better, without letting the process break as you scale.
We build the recruitment and workforce platforms that read, score, and explain every candidate, keep agencies and enterprises working on one system without seeing each other's business, and treat the decisions the software makes about people as the regulated decisions they are.
The constraint
On a hiring platform the largest group of people are not the customers. Candidates outnumber recruiters by orders of magnitude, and a CV is one of the densest personal records a person ever produces. Full name, address, phone, every employer, every date, qualifications, work rights, salary expectation. Most of those people never signed up for anything. They applied for a job. That has two consequences. The data is directly saleable in a way most business data is not, and the person most likely to take it already has a valid login. And the decisions the software makes about those people are regulated in a growing number of jurisdictions, whether or not anybody intended them to be.
One of the hiring platforms we have built, and the constraint it turned on.
Hiremii, now AQYR, an AI recruitment platform
Most multi-tenant platforms are built to keep tenants apart. This one has to let them across the boundary on purpose. An external agency works a client company's roles and needs that client's jobs, candidates, notes, and email history, and none of it for any other client on the platform. Two competing agencies can be working the same employer at the same time.
So access is a grant that passes four gates. A client decides whether agencies can find them at all, approves each connection individually, the agency names which of its own recruiters staff the account, and access is checked against the connection as it currently stands rather than as it stood when the session began.
A recruiter removed from an account loses it on their next request rather than their next login, which is the difference between revocation and a request to please log out.
AQYR is listed on the ASX.
The full set of our work is in our case studies, including platforms in adjacent sectors that solved the same access problems.
What we would expect to deal with on your platform
Not a service list. Four problems that show up on most hiring platforms, and the decision we made when each showed up on ours.
Recruiters do not choose what candidates send them. Files with a real text layer, scanned pages with none, and photographs of printed pages all arrive, and a general-purpose model reads a two-column resume as nonsense because a resume is a layout as much as a document. Reading is a ladder rather than a parser, and what comes out is a structured profile rather than a file.
A score nobody can explain is a score nobody can defend, because a recruiter has to justify a shortlist to a client. So every ranking opens into its reasoning, and the weights belong to the recruiter rather than to us.
Scoring arrives in waves. Post one job or change a role's requirements and thousands of candidates need scoring in the same second, so nothing calls the engine and waits, and a candidate without a score is invisible to the recruiter rather than merely late.
The same person arrives four different ways, through a job board, an ATS sync, a bulk import, and a recruiter's mailbox, rarely with the same details. Reconciling rather than re-inserting is a privacy control before it is a data quality one, because a person fragmented across four records cannot be given a straight answer about what is held on them.
Fairness, and what we do and do not claim
A hiring platform makes decisions about people's livelihoods, and in a growing number of jurisdictions those decisions are regulated whether or not anybody intended them to be. Automated employment decision tools face bias audit requirements, candidate notification duties, and disclosure obligations, and the direction of travel is toward more of that rather than less.
A model does not need to be given a protected characteristic in order to act on one. Postcode, education history, employment gaps, phrasing, and language all carry signal, and a ranking model trained on who was hired before will reproduce the pattern of who was hired before. Removing the field does not remove the signal.
Matching is built on what the candidate evidenced and what the role requires, rather than on similarity to previous hires.
Every ranking opens into its reasoning, with the contributing factors visible, so a recruiter can see why somebody surfaced and defend it.
The weights belong to the recruiter, adjustable per role, so the ranking reflects what matters for that hire rather than what mattered on average across a training set.
Recruiters decide. The platform ranks and explains, and no candidate is rejected by the system.
Which inputs produced a recommendation is recorded, so a question about a specific candidate has an answer rather than a shrug.
The boundary, stated plainly
We build the mechanisms that make a ranking explainable and auditable. We do not claim a platform is unbiased, and we do not conduct the independent bias audits that some jurisdictions require. Those are a separate piece of work with a qualified third party, and a supplier who claims otherwise is making a claim their client will be asked to evidence.
Candidate data, and who it belongs to
The people most exposed by a hiring platform are the ones with no account on it. A candidate database is directly saleable, which is not true of most business data, and the person most likely to take it is not an outsider, it is somebody who already has a valid login, often shortly before they leave.
So the structured profile rather than the original file is what everything downstream reads, which keeps the source document out of most code paths. Sensitive candidate fields are encrypted at the application layer with keys managed separately. Client credentials for job boards, ATS systems, and mailboxes are held centrally and retrieved at runtime, so a client's own credential rotates without a deployment, which matters considerably more when the credential belongs to the customer rather than to us. And access patterns are monitored rather than only access rights.
Candidates who should not be approached carry a flag and a reason, so a decision made once is enforced by the system rather than remembered by a person.
Which trust services criteria this work is judged on
Privacy, which is the criterion this platform lives on and a different thing from confidentiality. It concerns the people the data is about, whether they know what is held, whether they have a say, and whether a request about them can be answered. On a hiring platform those people are candidates who never signed up. That is why duplicate merging is a privacy control rather than a data quality one, and why a person fragmented across four records is a problem before anybody asks about them.
Confidentiality, which is the four-gate access model. Six user types on one platform means the question of who can reach what is asked on every screen, and answering it in one place is what makes it answerable at all.
Processing integrity, on the scoring path. Every score has to be attributable to the inputs that produced it, and a candidate without a score is invisible rather than late.
The boundary, stated plainly. The control set is designed against the criteria rather than mapped to them afterwards. That is a statement about how a platform was built, not a claim to hold an attestation, and where a client needs one, the work is theirs to complete with an auditor. We don't claim certifications we don't hold.
What this costs to run
Four things a finance leader should know, written about our work rather than about the industry.
Recruiter time moves from reading to deciding. Every CV arrives read, scored, and explained, so the expensive hour is spent on judgement rather than data entry.
The candidate database becomes an asset rather than an archive. A talent pool that stays current turns sourcing cost into something paid once rather than every time a vacancy opens.
Advertising is one action rather than six, because board-specific requirements are handled by the platform, which removes a per-job admin cost that scales with every role.
Throughput scales with workers rather than with engineering. Handling more volume is a capacity decision, not a rebuild.
What the platform actually does
Structural facts about the build rather than measured results. Every one is checkable from the product.
How you'd work with us
Pick the level of ownership that suits you.
Staff augmentation
Add senior engineers with hiring-platform experience to your team.
Dedicated team
A committed team that runs like your own.
Full delivery
Hand over the build and we deliver it end to end.
Frequently asked questions
How does the matching actually work? Can a recruiter see why somebody was ranked?
Matching is built on what the candidate evidenced and what the role requires, scored across multiple dimensions with weights the recruiter adjusts per role. Every ranking opens into its reasoning with the contributing factors visible, so a shortlist can be explained to a client rather than defended with a number.
Does the AI reduce bias?
We don't claim that, because it is a claim our clients would be asked to evidence. What we build is the mechanism: matching on evidenced skills rather than similarity to previous hires, rankings that open into their reasoning, weights that belong to the recruiter, recorded inputs behind every recommendation, and a platform that ranks and explains while people decide. The independent bias audits some jurisdictions require are a separate piece of work with a qualified third party.
Can you support agencies and enterprises on one platform?
Yes, including two competing agencies working the same employer at the same time. Access is a grant that passes four gates, scoped to the client relationship and checked on every request, so a recruiter removed from an account loses it on their next request rather than their next login.
Will it integrate with our ATS and job boards?
Yes. We integrate with ATS platforms, job boards, and recruiter mailboxes, with board-specific posting requirements handled by the platform and every arrival route reconciled into one candidate record per person.
Building a hiring platform that has to be fast, fair, and defensible?
Tell us what you're building, and we'll tell you honestly how we'd approach it.