AIOrders

Overview

A partnership with a sales-led founder to architect, build, and scale an AI-native B2B SaaS from nothing to a profitable business — acting as the technical half of the company rather than as a vendor to it.

The problem

The founder had genuine market pull and no technical organisation behind it. The risk was never demand; it was building something that could survive its own growth. Order handling that worked manually at ten customers would not survive a hundred, and every month spent on the wrong architecture was runway that would not come back.

What we built

Agentic order automation

Pipelines that ingest, interpret, and act on incoming orders, replacing the manual handling that capped how many customers could be served.

AI infrastructure

The model, retrieval, and evaluation layer the product depends on, owned as infrastructure rather than assembled per feature.

Platform architecture

Foundations chosen for the shape the business was growing into, so scaling was a capacity question rather than a rewrite.

Metric instrumentation

Core business metrics wired in from early, because roadmap decisions were being made against them.

How we approached it

• Own the outcome, not the ticket — accountability sat on business metrics
• Architect for the growth curve the founder was actually on
• Agentic automation where it removes a bottleneck, not everywhere
• Ship against runway; every architectural choice was a time trade

Outcome

An AI-native B2B SaaS scaled from zero to profitability, with agentic automation at the core and the technical organisation to keep extending it.