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From cold list to booked demo, without a human in the loop

Autonomous SDR that replaced a 6-person outbound team for a Series B SaaS

The client
Company · Vertical B2B SaaS operator (illustrative)
Industry · B2B SaaS · workflow tooling
Size · 48 employees, Series B
Region · North America + EMEA
Stage · Post-PMF, scaling GTM
Illustrative visual for the From cold list to booked demo, without a human in the loop case study
12×
Lead → meeting rate
<45s
Median response time
184
Qualified demos / mo
$46k
Monthly cost saved

A vertical SaaS operator was burning ~$52k/month on outbound SDRs with a 3.1% meeting rate. We shipped an autonomous sales-qualification agent that enriches, scores, personalizes and books — end-to-end, no touch.

01
The Challenge

What was breaking

  • Six SDRs cranking through Apollo lists at a 3.1% meeting-book rate — most of their day spent on manual research and copy-paste.
  • Response SLA on inbound demo requests was creeping past 6 hours; leaders were losing meetings to faster competitors.
  • Territory coverage was uneven — high-fit accounts in EMEA sat untouched for weeks between rep rotations.
02
The Approach

How we built it

  • Built a research + scoring layer that pulls firmographic, tech-stack and hiring signals for every inbound and outbound lead in under 8 seconds.
  • Trained a fit model on the client's last 24 months of closed-won and closed-lost deals to score every lead on a 0-100 ICP index.
  • Composed personalized first-touch sequences with an evaluator that rejects generic openers — every draft must pass a rubric before it sends.
  • Wired direct calendar handoff via Cal.com so qualified prospects self-book into the correct AE's calendar without a rep in the loop.
03
The Architecture

Under the hood

  • Ingestion: inbound webhook + outbound Apollo pull
  • Enrichment: Clearbit, Apollo, LinkedIn, hiring-signal scraper
  • Scoring: fit model + intent model, cached in Postgres
  • Reasoning: GPT-class LLM with rejection-sampling evaluator
  • Delivery: HubSpot Sequences + Cal.com handoff
  • Observability: every run traced, replayable, scored
The Impact

What changed for the business

+1,433%
Qualified demo volume
12 → 184 demos / month
−88%
Cost per qualified meeting
3.1% → 37%
Reply-to-meeting conversion
24/7
Coverage across timezones
The 14-Day Blueprint

How it shipped

Day 1–3
AI Audit

Mapped the existing outbound stack, pulled 18 months of CRM data and defined the ICP fit rubric with the sales leader.

Day 4–9
Sprint week 1

Shipped the enrichment + scoring pipeline and a shadow-mode agent that drafted (but did not send) replies for human review.

Day 10–14
Sprint week 2

Turned on autonomous send with guardrails, closed-loop evals on every draft, and Cal.com handoff for booked meetings.

Day 15+
Handoff

Transferred prompts, evals and the operator dashboard. The client's RevOps lead now owns tuning; we run the SLA.

Stack shipped
GPT-class LLMHubSpotApolloClearbitCal.comSupabase
Verified voices

What operators said

“It's replacing an entire outbound team — but the part I actually love is the traceability. Every meeting on my calendar, I can see exactly why the agent thought this lead was worth my time.”
Marcus Halden Verified
VP of Sales · Vertical B2B SaaS
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Testimonial 1 of 3: Marcus Halden, VP of Sales at Vertical B2B SaaS

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