LOCATION
Houston, Texas with 40+ locations across North America
CONTRACTOR TYPE
Specialty
TRADE
Scaffolding, Insulation, Coatings and Linings, Fireproofing, Painting, Abatement
NO. OF EMPLOYEES
6000 field | 200 office
INTEGRATIONS
Apache supports complex industrial job sites with high-volume craft labor. With roughly 6,000 field employees across locations and hundreds of office staff supporting operations, timekeeping is not an administrative task. It’s a foundation for payroll accuracy, customer trust, and operational control. It is also the input layer for everything Apache wants to do next with AI.
Kurtis Kim, VP of Information Technology at Apache Industrial, led the technology perspective on solving this: getting accurate information from the field, tightening verification, and creating a data trail that stands up to scrutiny, so payroll runs cleanly, disputes are defensible, and AI outputs can be trusted.
CHALLENGES
When Time Data Isn’t Verifiable, Everyone Pays for It
Before SmartBarrel, Apache faced issues common to large industrial contractors: buddy badging, ghost badging, and manual time-tracking workflows that created gaps in accuracy. Customers challenged whether crews were actually on site at specific times, and the team did not have a fast, verified way to respond. Missing details like lunch breaks added manual cleanup, and the burden of correcting time and interpreting contract requirements fell heavily on timekeepers.
Apache needed a reliable way to verify attendance, reduce administrative burden, and standardize time tracking across many locations without pushing more work onto timekeepers and foremen.
Key challenges included:
- Buddy badging and ghost badging, creating inaccurate time records and overpayment risk
- Manual sign-in/sign-out, leaving gaps (including lunch breaks) and driving weekly cleanup
- Customer disputes around jobsite presence, often hearing “your guys aren’t on site at this particular time.”
- Hours spent by payroll admin and foremen to correct entries and interpret contract differences
A growing need for data integrity as Apache rolled out its AI strategy (accurate inputs required for reliable outputs)
SOLUTION
Geo-Fencing + Facial Verification With End-to-End Timekeeping Automation
SmartBarrel delivered the visibility Apache needed: not only who clocked in, but who was on site in real time, with time classified in a way that matches how Apache runs projects and how customers evaluate T&M billing. Discussing the business impact, Barron said:
SmartBarrel gave Apache a field-first system built around verification and scalability. Instead of relying on manual sign-ins or retroactive corrections, Apache moved time capture closer to the source: the field.
Describing the shift, Kim said:
"The onus used to be on our timekeepers to put the information in, correct the information, know the contracts and do all the work. We’ve moved that data to the field and have supervisors and project managers responsible for their employees.”
SmartBarrel enabled:
- Geo-fencing to confirm punches occur on site
- Facial verification to confirm identity at clock-in/out
- Automatic punches so times are exact, not reported after the fact
- End-to-end timekeeping automation, allowing employees to punch in/out directly from the field
- The ability to accurately capture worker lunches
- Flexibility for real-world scenarios (errands, reassignment, contract differences)
RESULTS
Accurate Field Time, Stronger Dispute Defense, and Cleaner Inputs for AI
Apache strengthened confidence in time records across thousands of employees. Leadership gained clearer visibility into who was on site and when, and the organization could respond to challenges with auditable data.
Key Results
- Reduced fraud and verification risk by addressing buddy/ghost badging
- Stronger dispute defense: “yes they were — and here’s where they were,” backed by data
- Less manual timekeeping work, particularly around missing lunch data and paper workflows
- Better operational awareness of where employees are and whether they are on site working
- Cleaner, contract-aware data that supports AI initiatives (accurate inputs → accurate answers)
“We know AI is coming fast and strong. Accurate information is the only way you’re going to get accurate data coming out of AI.”
The SmartBarrel Advantage
Verified, AI-Ready Timekeeping at Apache’s Scale
For Apache, SmartBarrel wasn’t just a timekeeping upgrade. It became the verification layer and data foundation the company needed to operate with confidence today and execute its AI strategy tomorrow. Curtis’s point is simple: AI moves fast, but it only works if the underlying information is accurate.
What mattered most:
- Accurate inputs for AI: clean, contract-aware time data so Apache can “ask the right questions” and trust the outputs
- Verification-first timekeeping: addressing buddy badging and ghost badging with defensible clock-in/out records
- Proof of presence: location and time data that supports “yes they were, and here’s where they were,” backed by an audit trail
- Field-first capture: employees punch in/out directly from the field, with better capture of details like lunches (less manual cleanup)
- Accountability closer to the work: supervisors and PMs responsible for their teams’ time, reducing burden on timekeepers
- Partner-level support: weekly collaboration with a team that listens and helps achieve operational goals
