The people your workforce actually talks to
Candidates and employees do not deal with a platform. They deal with Maria, Daniel and Clare, who say they are AI in the first message, hand over to a human whenever anyone asks, and share one memory of the person they are talking to.
Maria
Reaches every applicant within minutes, screens and interviews by voice or chat, and coordinates the whole schedule.
Meet Maria →Hiring
Daniel
Collects and verifies documents, generates offers, registers new hires in your systems, and checks in through the first weeks.
Meet Daniel →Onboarding & compliance
Clare
Runs monthly conversations, surveys and exit interviews, turning what people say into insight your team can act on.
Meet Clare →Engagement & insights
What they handle, in the order it happens
Not features. The work that piles up between a role opening and someone's last day, the part that gets rationed when a team is stretched.
Step 1 · Maria
Answering and screening applicants
Every application gets a reply, whether it arrives at 11pm, on WhatsApp or through a QR code in a shop window. Then a real screening conversation by voice or chat against the criteria for that role at that site.
Under 2 minutes from application to first contact
What that has been worth
Read the case studies →−65%
time to hire in security and facility services: 21 days cut to under a week
620+
retail stores onboarding on one process, documents collected and filed end to end
42% → 39%
first-30-day churn, client-reported. First-week check-ins catch what exit interviews explain too late
Three names, seventeen specialists
A name is what a person answers. Behind each one, a team of specialist agents splits the work: screening, scheduling, verifying, registering, checking in. Every exchange writes into the same context layer, so nobody is ever asked the same question twice.
Channels
The same person, all the way through
Maria's candidate becomes Daniel's new hire becomes Clare's employee and, one day, Clare's leaver and Maria's best rehire. What one learns, the others already know: an exit interview changes what the next screening call asks, a first-week problem changes what onboarding checks.
A no in January is a yes in March. The people you do not hire today stay in a pool that remembers why the fit was not right yet, and Maria reopens the conversation when something that suits them opens up.
Where they stop and your team takes over
A support tool, never a decision-maker. These limits are built into the platform, not left to a prompt, and they are the reason people answer honestly.
They say they are AI. First message, every time.
Nobody has to work out who they are talking to. Anyone who would rather have a person gets one, and the handover carries the full context so nothing is repeated.
They prepare the decision. They never take it.
Agents assemble the evidence: answers, transcripts, availability, documents. Your team approves. Recommend-then-approve is built into the platform, not asked for in a prompt.
No emotion analysis. Not now, not later.
What people say is recorded. What a model guesses they feel is not. Inferring emotions at work is prohibited under the EU AI Act, and it would poison the honesty the whole thing depends on.
Every evaluation can be reconstructed
Criteria, transcripts, timestamps and human approvals logged end to end, with independent bias audits run monthly. ISO 27001 · SOC 2 · GDPR.
See them on your real processes
From analysis to live deployment in weeks, on your roles, your channels and your systems.
Book a demo →