How a US logistics company reduced manual scheduling by 70% and improved on-time deliveries with novagentum.

Solutions

novagentum.ai deployed an Agentic AI Agent that:

• ingests orders, ETA and traffic data, and driver rosters
• plans optimal routes
• assigns and reassigns tasks autonomously when exceptions occur
• notifies customers and drivers with context-aware messages. The agent coordinated with the clients TMS and CRM via secure APIs.

Implementation Timeline

12 weeks from kickoff to controlled rollout (pilot across one region), then phased rollouts across all regions in 3 months.

Measured Results (first 6 months)

• Manual scheduling time reduced 70% (operations headcount reallocated)
• On-time delivery rate improved +18 percentage points
• Fuel & routing cost reduction ~12% (optimized routing)
• Customer support inquiries related to scheduling down 40%

How we did it

• 1. Needs analysis & data audit (week 1–2)
• 2. Agent design + simulation against historical routes (week 3–6)
• 3. Integration with TMS & driver app + sandbox testing (week 7–9)
• 4. Pilot & learn (week 10–12)
• 5. Scale with monitoring and KPI dashboards (months 3–6)