ShippedSales AISales DevelopmentB2B SaaSOutbound
// build study

PipelineIQ

An AI SDR platform that scores every lead for fit, runs multichannel sequences across email, LinkedIn and call, drafts the replies, and books the meeting.

Client:B2B SaaS sales org (NDA)
Duration8 weeks
ScopeMVP product design and front-end build of the Outbound board and single-lead detail experience, backed by a lead fit-scoring model and a multichannel sequencing engine.

// The Outbound board — reply-rate and pipeline KPIs, the Sent → Opened → Replied → Booked funnel, and leads ranked by AI fit score.

// the numbers

Figures from the engagement, shared under NDA.

We publish them unchanged and can’t break them down any further here. The reference build you can open runs entirely on sample data.

2,140Leads in sequence
11.4%Reply rate
38Meetings booked
$412KPipeline generated
01In brief

If you read one part of this page, read these 4 lines.

  • Scores every lead 0–100 for fit before a single send goes out
  • Runs email, LinkedIn and call as one sequence that pauses the instant a lead replies
  • Drafts the next-touch reply that books the meeting — with a confidence score, not false certainty
  • One outbound view of funnel, sequences and reply sentiment for the whole SDR team
02Overview

What it does — and which part of it we built.

PipelineIQ gives outbound sales teams one engine that turns a cold list into booked meetings.

It grades every lead 0–100 for fit using ICP, intent, seniority and tech-stack signals, runs timed multichannel sequences across email, LinkedIn and call, and drafts the next-touch reply that moves the deal forward — auto-pausing the sequence the moment a lead responds. BuildspaceLabs designed and built the MVP front end — an Outbound board for the team's funnel and a per-lead detail view for the SDR working the deal — turning a fit-scoring model and a sequencing engine into a workflow an SDR can run all day.

03The screens

Every screen here is from the reference build, not the client’s system.

The captions say what you are looking at. Every name and record on them is sample data.

04Outcomes

What the engagement left the client with.

  • Delivered a production-quality MVP of the Outbound board and lead detail view in an 8-week engagement
  • Consolidated fit scoring, multichannel sequencing and reply drafting into a single SDR workflow
  • Gave sales leadership a real-time view of the outbound funnel, reply rate and pipeline generated across the team
  • Established a reusable design system (fit-score bars, status pills, sequence-step dots, compose cards) for the product's next surfaces
05How it is built

The stack was picked per constraint, not per house habit.

7 technologies across 4 layers — the shape of the stack follows the problem.

AI & ML
Python · scikit-learn fit model
Frontend & Mobile
Next.jsReactTypeScriptTailwind CSS
Data & Infrastructure
PostgreSQL
Backend & APIs
FastAPI
Every feature in the build (6)
  • Outbound board with live reply-rate, meetings-booked and pipeline KPIs above a Sent → Opened → Replied → Booked funnel
  • 0–100 AI fit score per lead across ICP, intent, seniority and tech-stack signals
  • Multichannel sequences weaving email, LinkedIn and call into one timed, auto-pausing flow
  • AI-drafted next-touch replies grounded in the thread and the lead's signals, with a confidence score
  • Reply-sentiment classification that routes positive replies to the SDR inbox and pauses the sequence
  • Lead detail with a weighted fit-score breakdown, sequence timeline, engagement signals and the mapped buying committee
// see for yourself

Don’t take our word for it — it is running in the frame below.

This is the same page the provenance block links to: our reference build for PipelineIQ, with its own look, copy and motion. Scroll inside it, or open it full-screen.

// more from the lab

A team that ships across the board.

36products in production
8industries served
68+technologies in play

Closest to PipelineIQ

// next

Building something in this space?

A 30-minute call is enough for us to understand your situation and tell you whether we're the right team. Usable version in the first two weeks if we are.