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Case study · autonomous lead generation

A week of prospecting, done before breakfast.

Finding high-value fitness creators used to take our client's team 40+ hours a week, and yielded fewer than 20 qualified leads. The lead engine we built produces 100+ scored, contact-verified leads per run. On its own, on a schedule, with nobody watching it.

System

Autonomous lead-generation engine

Sector

Fitness & wellness · creator economy

Replaces

40+ hours of manual prospecting a week

Status

In production, runs unattended

Client and platform names withheld. We name clients only with their written permission. Every number on this page comes from the production system.

The problem

Lead generation in the creator economy is a qualification problem wearing a discovery costume. Anyone can compile a list of accounts with big follower counts. Working out which of them are genuine professionals, with real audiences, worth a partnership, and reachable at a working email address? That's the 40-hour week.

The manual workflow (search, browse, vet, dig for contact details, draft outreach) cost more than time. It capped the pipeline: the team could only convert what it had hours left to find.

What the engine does

Discovery, qualification, contact, draft. End to end, unattended.

Discovery beyond hashtags

The engine finds creators by analysing the network around known high-value accounts, surfacing people a keyword search never sees, then filters them against the client's actual qualification bar.

AI-verified, 100-point scored

Every candidate is checked by AI for genuine professional credentials and scored on a 100-point quality scale, so the output is a ranked shortlist, not a raw list.

Contact details that hold up

A multi-tier discovery waterfall finds the email; a seven-stage validation protocol proves it's deliverable. Leads without a verified contact route never reach the output.

Outreach, drafted and waiting

Each lead arrives with a personalised outreach draft calibrated to who they are. Reviewed and sent by a human, never fired blind.

What we won't publish is the how. The discovery method, the scoring model and the validation stack are the client's competitive edge, and ours. If you want to see it running, ask for a demo.

The numbers

100+

qualified leads per pipeline run

Each one discovered, credential-checked by AI, scored for quality, contact-verified and paired with a personalised outreach draft, before anyone on the sales side lifts a finger.

<0.5%

email bounce rate

Every address passes a seven-stage validation protocol before it's allowed into the system. Sub-half-a-percent bounce is the deliverability gold standard. Most purchased lead lists run 5-10%.

40+ hrs

of weekly manual work replaced

The manual version of this workflow (searching, vetting, finding contact details, drafting outreach) consumed a full working week and produced fewer than 20 qualified leads.

Why it holds up in production

An autonomous system is only useful if you can trust it while you're not looking. This engine is built the way we build everything: each stage commits its work independently, so a failure late in a run never loses what came before; every AI judgement is bounded by validation gates rather than taken on faith; and anything irreversible, like outreach actually being sent, stays behind a human decision.

That's the difference between automation you babysit and automation that quietly compounds: the pipeline has run on its schedule since launch, and the humans only touch the output.

Drowning your own team in prospecting?

Lead generation is where automation pays back fastest. See how we scored an entire B2B prospect book in the lead-intelligence case study, or compare your options in agency vs in-house vs no-code.

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