We built Pipelark because reps deserve better than a list.
Founded in Denver in 2022, Pipelark started as a RevOps consulting project that turned into a product when we kept solving the same problem for every client.
From RevOps frustration to product
Before founding Pipelark, Caitlin Brooks spent four years running revenue operations at a fintech company in Denver. Every morning, the sales team opened HubSpot and worked the inbound queue from top to bottom. Not because top-to-bottom was correct — it was just the default. No scoring, no intent signals, no way to know that the lead on row 47 had just visited the pricing page twice and opened every email.
Caitlin started building scoring models on the side: first a spreadsheet that weighted firmographic fields, then a Python script that pulled activity data and re-ranked the queue each morning. Reps who used it closed faster. Three consultants in her network asked for the same thing. That's when she understood: this wasn't a RevOps project. It was a missing product category.
Pipelark was co-founded in Denver in 2022. We closed a $500K angel round in late 2025 to grow the engineering team. We are four people. We are not building a full revenue intelligence platform — we are building the best inbound lead prioritization tool for B2B revenue teams that can't afford Gong and don't need it. That focus is deliberate.
Four people building one focused product.
Former RevOps lead at a Denver fintech. Built the first scoring model in a spreadsheet because no existing tool surfaced intent signals in the CRM queue. That spreadsheet became this product.
Previously built CRM data pipelines at a growing B2B software company. Knows how to make an OAuth connection feel like it was always there.
Former AE and sales ops manager at a high-growth B2B SaaS company. Owns customer onboarding and ICP configuration — the person who gets new teams to first scored lead in under a day.
Built NLP classification and behavioral scoring systems at a martech company. At Pipelark, he designs the intent signal pipeline — the layer that decides when a prospect's activity pattern is a buying signal versus background noise.
What guides every decision
Every product decision at Pipelark runs through three filters. If a feature doesn't pass all three, it doesn't ship — even if it looks impressive.
Reps first
Decisions are made by what makes the rep's day easier, not what looks good in a dashboard. If a feature requires reps to change their workflow, we rethink the feature.
Explainability over accuracy
A score with a reason your rep understands beats a black-box prediction every time. An 89 with three legible reasons will get acted on. A 96 with no explanation will get ignored.
Setup in minutes, not sprints
If a RevOps team can't deploy Pipelark in a single afternoon without engineering help, we've failed. Every new feature is evaluated against this constraint first.
Talk to Caitlin directly
We're still small enough that Caitlin joins most demos herself. If you want to show us your CRM and see your own leads scored live, that's the demo — no slides, no generic data.