Slingapult watches the LinkedIn voices your buyers follow, captures everyone who engages, and scores them for fit and intent — so your CRM fills with ranked leads and the reason they’re worth a message.
No enrichment · no stored LinkedIn credentials · invite-only preview
Curated sourcing in, ranked pipeline out — and it gets sharper every week.
Hand-pick creators, competitors, and company pages worth monitoring — no noisy keyword search.
Pull commenters (with their comment) and reactors from each new post via no-cookies actors.
Claude classifies comment intent; rules score ICP-fit from the scraped headline + engagement velocity.
Ranked leads land in your inbox and sync to HubSpot with the why-now context attached.
Mark won/lost and the scoring weights sharpen to your real pipeline over time.
Every lead carries a 0–100 score split across intent, fit, and velocity — plus human-readable chips like “solution-seeking”, “ICP fit: VP+”, and “3 posts / 14d”.
Won/lost outcomes feed back into the weights, so the model learns the shape of your real pipeline instead of a generic guess.
Reusable, industry-specific voice packs let a new workspace start from the signal-rich accounts that actually matter.
Slingapult only uses no-cookies capture actors — we never ask for or store your LinkedIn credentials. Leads are LinkedIn-first: a profile, name, title, and company, with no email enrichment. Outreach happens where the conversation already is.