INTELLIGENCE PILOTS
Proven Across Three Environments. Built for Yours
Three operational environments. Three distinct problem sets. One platform that connects your data, surfaces your risk, and acts before the damage is done.
Frameworks developed for client requirements; not deployed under a commercial contract. Results reflect pilot-scope demonstrations.
01/ HEAVY INDUSTRY & LOGISTICS
The DeLong Co.
Safety Intelligence Pilot—Clinton, Wisconsin
[PREDICTIVE MAINTENANCE]
[OSHA COMPLIANCE]
[SAFETY INTELLIGENCE]
THE PROBLEM
The DeLong Co. is a sixth-generation family business and the largest U.S. exporter of containerized agricultural products. Operating out of Clinton, Wisconsin, their facilities run complex equipment where downtime costs thousands per hour and creates direct OSHA exposure. Safety documentation was manually reviewed. Certifications expired without automated notification. Incidents like grain bin engulfment hazards and electrical arc flash near-misses were logged after the fact it was not flagged in advance. The data to prevent these failures already existed. Nobody was connecting it in real time.
WHAT WE ENGINEERED
SOL AI developed a Safety Intelligence Pilot tailored to DeLong's operational environment. The system automates ingestion of safety reports, incident logs, and certification records. This turns hours of manual data retrieval into an automated daily intelligence layer. Automated hazard tracking for grain bin engulfment and electrical arc flash incidents. Proactive certification alerts before expiration, not after. PPE training compliance monitoring across 12 employees with overdue flags surfaced to supervisors automatically.
WHY THIS TRANSFERS
The architecture built for this engagement is now the template SOL AI uses to demonstrate risk mitigation in any high-value, heavy-equipment environment. This includes crucial industries such as defense logistics and construction operations. If the system can flag hazards before they become OSHA incidents at this scale, it can handle your operation.
12
Employees Monitored
<5s
Data Retrieval vs. Hours Manual
10
Training Modules Tracked
3
Active Incidents Flagged
The Poobel Company
Fleet Integrity & Dispatch Intelligence— Union, NJ
[REAL-TIME DISPATCH] [LOGISTICS OPERATIONS] [FIELD OPERATIONS]
THE PROBLEM
Poobel operates waste management fleet operations across the dense urban corridors of Union, NJ. Field delays weren't being reported to dispatch in real time. Route inefficiencies were invisible until they became missed stops. Operational data, driver positions, route completions, and scheduling conflicts. These all existed but lived in data silos. No one was seeing the full picture until it was too late to act.
WHAT WE ENGINEERED
SOL AI built a Digital Twin of Poobel's fleet operations. This was a real-time dispatch intelligence layer that surfaces driver positions, route completion percentages, and delay alerts on a live map dashboard. Driver Marcus was flagged 10 minutes behind schedule due to traffic at 3:45 AM, before a single stop was missed. Active driver tracking against stop quotas updated continuously. Fleet overview with geospatial routing across high-density urban corridors.
“Four active drivers. Zero real-time visibility. Every delay was invisible until it was already a problem”
