Recruitment and search

AI agents for recruitment
and executive search.

The role jams in screening and the good candidate answers whoever called first. Labs designs the agent on your role, screening and shortlist flow, connected to the systems the firm already uses.

What jams

Response time decides the role, and it depends on someone being free.

CVs arrive all day, the client chases the shortlist and the senior consultant is the only one who can judge. Roles are not lost for lack of candidates. They are lost in the queue.

  • 01The role is lost on response time, not on the lack of candidates.
  • 02Screening depends on the senior consultant, who is the bottleneck of every search.
  • 03A good candidate is left without a reply and the employer brand pays for it.
  • 04The client chases the shortlist and nobody has half an hour to build it.
Use cases

AI agents for every area
of your operation.

Hendu connects the systems and channels your company already uses and keeps the operation's context: what was agreed, with whom, and what is still missing. The agents work on top of that layer, each one as the right arm of an area. You step in to approve.

01Marketing

The firm gets found by the role it knows how to close.

The agent answers whoever arrives from the site, the network and referrals, understands the role and seniority, and shows which channel brings searches that become contracts.

  • Answers site, network and referral contacts at once.
  • Qualification by role, seniority and urgency.
  • Shows which channel brought a search that became a placement.
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What changes

The same team,
operating at another level.

This is not about your team working harder. Chasing, checking, handing over, remembering: that work, the one that eats their day today, starts happening on its own, following your rule and under your eye.

Efficiency

What took a day starts taking an afternoon. Not because someone ran faster, but because the step that jammed everything stopped existing.

Productivity

People go back to the work that needs people: deciding, negotiating, solving the hard case. The rest arrives finished, waiting to be reviewed.

Cost

Growing stops meaning hiring in the same proportion. The operation absorbs more volume on the structure it already has.

Margin

Less rework, fewer forgotten commitments, fewer missed deadlines. That is margin that was already yours and was leaking on the way.

Scale

What works in one team is repeated in the others the following week, because the rule is written down, not held in one person’s head.

How it works

Seven days.
One process, live.

Not a six-month project. One process at a time. And you see the first one working before you decide on the second.

Days 1 and 2

We map the rule

We sit with the people who do the work: the exceptions, the limits, who decides what.

Days 3 to 5

We build

The agent is built in your vocabulary, on the systems the company already uses.

Days 6 and 7

It goes live

It runs on real work, supervised, and is adjusted in use before it leaves our hands.

After

It expands

With the first one running, the second costs less: context and governance already exist.

Why the Labs exists

AI is already in your company.
The work has not changed.

Someone on your team opened ChatGPT today. It helped write an email, summarise a document. But the payment nobody chased, the deadline nobody checked and Friday's report are still done by hand, exactly as before. It is worth understanding why. That is what the Labs fixes.

Ask an off-the-shelf AI tool for a payment reminder and it writes a flawless email in ten seconds. But it does not know how much that client owes, what was agreed with them last week, whether your finance team already chased them yesterday, or that your company never chases before five days overdue. You are the one who knows all that. So you type in the context, read what comes back, fix what is wrong. And you end up spending nearly as long as writing it yourself. The real work was never writing the email. It is knowing what has to be in it.

The screen

This is where the agents live.
You approve, they do the rest.

The agent the Labs builds does not live in a separate window. It comes into this screen, alongside the rest of your team’s work: this is where it shows what it did, what it proposes and what is waiting on your go-ahead.

MONDAY, AUGUST 30Full day
Good morning, Laura.
SINCE YESTERDAY AFTERNOON3meetings transcribed9new commitments4no reply
How the day breaks down
8am7pm
8am – 12pmThree meetings back to back. Most of today’s commitments come from here.
12pm – 4pmThe clearest block of the week. Good for clearing what is stuck.
4pm onwardsTwo deliveries due at end of day. After that Friday closes clean.
Moving as expected14 commitments on trackVitrine: kickoff bookedtomorrowLima: proposal acceptedyesterday
Today's briefing
Priority actions
Agent flow3 activeCustomer follow-up3/5Chasing open items3/5Contract renewal2/6
Decisions with traction14Moving4Late2Stuck

Sector not listed?
The conversation starts from your process.

Half an hour to find where it hurts in your operation, and a picture of what AI changes in it. If it makes sense, the first agent is live in seven days.