[ PRODUCT · TALENT & CRM ]

AI Talent & CRM

Hire the team and run the pipeline in one product, because both are the same problem wearing different labels.

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−45%
Time-to-hire
28%
Faster sales cycle
[ Overview ]

AI Talent & CRM

Hire the team, then run the pipeline — sourcing and revenue in one product.

AI sourcingResume screeningLead scoringPipeline forecasting
[ What it does ]

Inside AI Talent & CRM.

Auto-screen

fit-scored shortlists

Interview ops

scheduler built in

Lead intake

dedupe & route

Forecast

pipeline made visible

Two funnels, one system

Recruiting and selling are structurally identical: a stream of inbound and sourced records, a scoring step, a sequence of conversations, and a forecast someone is accountable for. Most organisations run them in two unconnected tools and reconcile by hand.

AI Talent & CRM treats them as one product. Sourcing and screening feed the hiring funnel, lead intake and scoring feed the revenue funnel, and both share the same scoring, deduplication and forecasting machinery underneath.

Screening that produces a shortlist, not a pile

Resumes are parsed and scored against the requirement rather than keyword-matched, so what comes back is a ranked shortlist with the reasoning attached — which is what makes it reviewable rather than something a hiring manager has to redo.

Interview operations are part of the product: scheduling, panel coordination and follow-up sit alongside the shortlist instead of in somebody's inbox.

A forecast built from what is actually there

Lead intake deduplicates and routes on the way in, so the pipeline reflects distinct real opportunities rather than the same company entered four times by three people.

Forecasting then works off that cleaned pipeline — stage, age, movement and scoring — to make the shape of the quarter visible rather than asserted in a weekly meeting.

Where the AI actually sits

It is worth being precise, because “AI recruitment software” covers everything from a keyword filter upwards. Here the model does three jobs: reading unstructured documents — resumes, job specs, inbound email — into structured records, scoring those records against a stated requirement, and summarising a history into something a person can act on in a few seconds.

Everything downstream of that stays deterministic. Stages, routing rules, ownership and permissions behave the way a system of record has to behave, so nobody has to wonder whether the pipeline moved because of a rule or because of a model.

[ Questions we get asked ]

AI Talent & CRM, answered.

Why combine recruitment and CRM in one product?

Because the two funnels behave the same way — intake, scoring, a sequence of conversations, a forecast — and running them in separate tools means reconciling the same companies and contacts by hand. One system removes that reconciliation.

How does AI resume screening work?

Resumes are parsed and scored against the actual requirement rather than matched on keywords, and returned as a ranked shortlist with the reasoning shown, so a hiring manager can review the judgement instead of repeating the sift.

Does it replace our existing ATS or CRM?

It can, or it can run alongside one. Which makes sense depends on what your current tools are already doing well — that is a scoping conversation, not a fixed answer.

Can a hiring manager see why a candidate was ranked where they were?

Yes. Each shortlist entry carries the reasoning behind its score against the stated requirement, so the ranking is something a hiring manager reviews and can overrule, rather than a number they have to take on trust.

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