Ambition
For over 15 years, Titan has grown consistently as a global geosynthetics solutions leader operating from Canada and the United States. The ambition: keep growing without the technology holding the company back.
Case study · Titan
The AI workforce that paid for itself 5x over.
Titan: North America’s fastest-growing end-to-end geosynthetics supplier, fabricator, and installer, built for 15+ years on a belief that was quietly capping its growth: that scale meant more headcount, not smarter systems.
The genesis
Where it started.
Target group
Titan’s field inspectors, report writers, new hires, and the clients waiting on the reports they produce.
The challenge
What stood in the way.
Titan’s status quo
After every site inspection, employees had to submit a detailed report of the findings, each one taking 3 to 4 hours to produce. Manual steps meant human error, which caused delays and customer dissatisfaction. Training a new employee on the process took several months.
A bottleneck on growth
Titan had been growing for 15+ years, but the technology hadn’t kept up, and this bottleneck was standing directly in the way of the next stage of growth.
The belief underneath the barrier: that speed and accuracy were a trade-off, and that the only way to grow throughput was to grow headcount.
Our strategic intervention
Three moves, in order.
- 01
Body: Process Mapping & Automation
Every action employees were taking was understood and converted into streamlined, automated processes using software robots (RPA).
- 02
Mind: Decision Encoding
Every decision employees were making (in the office, with the customer, in the field, entering data) was encoded into AI, so it could help employees make the right call.
- 03
Soul: Employee Buy-In
We dug into the behaviors and workflows of each employee and brought them into confidence that this technology was here to help, not replace them. Even with sponsorship from the executive team, this would not have worked without buy-in from every person on the team.
Execution & innovation
How it was built.
Parallel AI system
Rather than ripping out the legacy system all at once, a parallel AI-driven system ran alongside it, preserving institutional knowledge while adding accuracy and efficiency.
Automated reporting
RPA-driven, AI-assisted report generation replaced hours of manual work.
New revenue stream
The new speed made a rush report delivery service possible: a revenue stream that didn’t exist before.
Results
What changed.
Report Time Collapsed
Reports that took 3–4 hours now take about 9 minutes, with higher accuracy.
Training Time Collapsed
New employees productive within a week instead of several months.
Strong ROI
400–500% return on the Phase 1 investment.
New Revenue
Rush report delivery launched as a new service offering.
By the numbers
- ROI
- 400–500%
- New report time (from 3–4 hours)
- 9 min
- Phase 1 duration
- 12 weeks
Budget
~$50K (Phase 1)
Timeline
12 weeks (Phase 1). Phase 2, a full legacy system overhaul, is underway.
Conclusion
Titan’s ceiling wasn’t the market, and it wasn’t the team. It was a belief that had never been tested: that the only way to grow throughput was to grow headcount. Once that belief moved, a 3–4 hour report became a 9-minute one, a months-long onboarding became a week, and Titan found a new revenue stream it didn’t have before, without adding people.
What’s next
Your story could be next.
See where you stand, then build the operation that compounds from here.