The client operates in the high-volume healthcare claims-processing sector — high-value, high-sensitivity work where accuracy is not optional. When a sharp rise in market demand sent claim volumes surging, the opportunity was immense. The infrastructure to meet it was not.
Their core system was a homegrown, 1990s-era case-management tool. Processing a single claim meant navigating 19 to 27 separate screens, clicking and re-entering the same data at every step. The operation could only scale in one direction: more claims meant more people.
And the people had run out of room. The business model was linearly dependent on human labour, and the office had literally run out of desk space for the staff needed to keep up. The company was turning away profitable work because it couldn’t fit more keyboards in the building.
The client came to us through a competitive tender with a narrow brief: connect their systems to external data sources. We won the work — and the diagnostic showed that a simple API pipe would solve almost nothing.
Roughly 80% of the daily workload was repetitive data entry and administrative click-work. Rather than spend years building the future platform while the backlog grew, we ran two tracks at once: automate the legacy mess now to free capacity immediately, and architect the cloud-native replacement in parallel.
- Every automation had to clear one rule before we built it — it had to save at least half a full-time role. If we couldn’t prove the return, we didn’t build it.
- A one-week break clause sat inside the R&D work, so the client could stop any path the moment it stopped making financial sense.
- And when they asked for risky open-AI chatbots inside a regulated environment, we said no and explained why. Each call reduced their exposure, not ours.
Every metric moved, and they moved together. The same team — with only about 20% more headcount — processed roughly three times the claim volume. Automation absorbed the equivalent of 30 full-time roles: capacity the business would otherwise have paid for in salaries and desk space.
Revenue grew 5× from the year the engagement began. The second building was never rented. Growth had been capped by processing capacity; once that ceiling lifted, the business could close more work at the same margins — and the gain landed in the P&L, not in a bigger payroll.
The software mattered less than what it freed people to do. Staff who had spent their days clicking through screens moved to the work technology can’t touch — time with the client’s own customers, the judgment-heavy decisions. As the results landed, the brief widened on its own: the automation led to a platform rebuild, the rebuild earned security certification, and the certification led the client to ask us to help stand up an adjacent line of business. They already had a CTO to keep the technology running; what they’d been missing was the seat that bridges business strategy and execution. Today that seat is ours.
