B2B SaaS is where most of our work sits. The pattern repeats: the product is good, the market is real, and growth has stalled behind an operation that cannot produce or measure pipeline reliably. Usually all three of those problems are present at once and each is blamed for the others.

Vertical SaaS has a particular version of this. When you sell into one industry, your total market is a finite list rather than an abstraction, and growth is capped by coverage rather than by size. Whether you have worked the whole list is a question with an actual answer, and most teams have not.

On the operations side, SaaS carries the reporting problems that come with recurring revenue: deal stages that drift from reality, renewals and expansion that sit outside the pipeline view, and a CRM that disagrees with finance on what was actually booked.

We work across all three: demand generation to build the pipeline, revenue operations to make it measurable, and AI implementation where a workflow can be genuinely improved rather than merely automated.

Where we help

  • Outbound pipeline into a defined vertical market
  • Whole-market coverage rather than sampled lists
  • CRM architecture for recurring revenue
  • Renewal and expansion visibility in the pipeline
  • Deal-stage definition and forecast accuracy
  • CRM and finance reconciliation
  • AI ticket triage and support automation
  • Follow-up automation and no-show recovery
$2.3M

in qualified pipeline sourced for a B2B SaaS client within a single engagement scope.

What We Have Delivered in SaaS

$2.3M

Pipeline from a 5,000 account market

For a vertical software company. The whole addressable market was treated as the working list rather than a sample, with outbound built on signal-based prospecting and structured follow-up. Sourced within one engagement scope.

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60%

Revenue growth in one quarter, no new hires

For a B2B SaaS business serving design and architecture professionals. Achieved by automating follow-up, eliminating no-shows, and routing every lead to the right owner instantly. Absorbed entirely by the existing team.

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78%

Of Tier-1 tickets resolved autonomously

For a global enterprise cloud platform, described by type rather than named. SLA compliance rose from 69% to 96% and support operational costs fell 44% in the first quarter. Delivered through our specialist operators.

The operations layer underneath

For a SaaS fintech, one engagement surfaced $52K per month in recurring unrecognised revenue, a $40K monthly gap between CRM and finance, and a database where 38% of reported leads were duplicates. These are the problems that make a SaaS forecast unreliable.

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Selling software into a market you can name?

Tell us the size of your addressable market and what your pipeline looks like against it. We will scope the gap and come back with a plan.

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