The problem

The hidden cost in your ops team

Every SaaS company at Series A and B has the same problem.

The team is smart. The tools are good. But somewhere in the operation there are 10–20 hours a week being spent on work that follows a pattern — and nobody has fixed it because it's never quite urgent enough to prioritise over everything else.

Until it is.

When you're at 30 people it's manageable. At 80 people it's a person's full time job. At 150 people it's a team.

The companies that break this pattern early — that automate it before it becomes headcount — have a structural cost and speed advantage that compounds for years.

That's what we build.

What we automate

What gets automated

Sales operations

Lead research and enrichment, CRM updates, personalised outreach drafting, follow-up sequencing, pipeline reporting.

Customer support

Tier-1 ticket triage and routing, draft response generation, knowledge base retrieval, sentiment classification, escalation logic.

Operations and finance

Weekly reporting automation, data reconciliation across tools, vendor communication summaries, invoice processing, expense categorisation.

Product and marketing

User feedback synthesis, competitor monitoring and alerting, release note drafting, content repurposing, social media scheduling.

Customer success

Onboarding checklist automation, health score monitoring, renewal risk flagging, QBR preparation.

How we deliver

The sprint model

Week 1

Scope and design

We map the workflow end-to-end with your team. Identify the inputs, outputs, edge cases, and integration points. Define the success metric. You sign off before we write a line of code.

Weeks 2–4

Build and integrate

We build the agent. Connect it to your existing tools (CRM, Slack, email, databases). Test against real data. Handle the edge cases your team would trip over.

Weeks 5–6

Handover

We hand over a running system — not a prototype. Full documentation. Monitoring in place. Your team knows exactly how it works and what to do if something breaks.

After

Two weeks of support included

Most clients expand to a second workflow or move into AI product engineering within 60 days.

Proof

What we've shipped

Series B SaaS · Sales ops · US
14 hours every Monday → under 2.
AI agent that pulls new leads, enriches them with company context, scores them against ICP, and drafts personalised outreach. Sales rep reviews and sends. Integrated into their existing CRM. Delivered in 5 weeks.
Series A SaaS · Customer support · US
Avg response time 4h → 22 min.
AI triage agent that classifies incoming tickets by type and urgency, routes to the right team, and drafts a first response. Support headcount held flat through 3× growth in ticket volume.
FAQ

Common questions

How is this different from Zapier or Make?

Zapier and Make connect tools and automate simple if-then logic. We build agents that can read context, make decisions, handle edge cases, and produce outputs that require judgment — not just trigger-action workflows. If your workflow requires understanding what something means, not just moving it from A to B, you need an agent, not a Zap.

What if the workflow is more complex than expected?

We scope it before we start. If complexity emerges during the build we discuss it with you before it affects timeline or price. We don't spring surprises at invoice time.

Do we need to change our existing tools?

No. We build around what you already use. The agent integrates into your existing CRM, communication tools, and data sources. You don't have to migrate anything.

How do we know it'll keep working?

We set up monitoring before handover. If the agent breaks or produces unexpected output, you'll know about it before your team does. We also include two weeks of support after handover.

What if it doesn't work?

We agree on a success metric before we start. If we don't hit it, we don't invoice for the full amount. We've never had to invoke this — but the protection is there.

Could our engineers build this themselves?

Yes. The question is whether you want your best engineers context-switching onto an AI ops problem they've never solved in production before — or staying focused on your core product. We've already solved the reliability issues, the integration edge cases, and the prompt engineering problems. You get the result without the distraction.

Have a workflow in mind?

Tell us what your team is doing manually. We'll map it in 20 minutes and tell you honestly if AI can fix it in 4–6 weeks.

Fixed price. Fixed scope. No surprises.