Section 01
Company: US logistics company — regional B2B logistics provider (200 employees)
Challenge: Manual route planning and dispatch consumed operations staff hours, caused frequent rescheduling, and created late deliveries during peak season. The company needed dynamic scheduling that could react to delays, driver availability, and client windows — without hiring large ops teams.
Section 02
Where the operational load actually moved
Dispatch teams rarely see a single-step fix. The meaningful shift happens when exceptions stop bouncing between spreadsheets and phone trees—and the agent can act inside the same systems of record the business already trusts.
Trend graph
Indexed manual dispatch hours
12-week rollout
Weeks are from program kickoff. The curve reflects combined design, integration, pilot, and scale phases—not a single feature launch.
Section 03
What we delivered, how long it took, and what changed
The work combined agent design, integrations, and a careful pilot so teams could trust automation before it scaled across regions.
System map
The agent stayed behind the same security model as existing TMS and CRM integrations—no parallel shadow database for dispatch truth.
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)
Section 04
Benchmarking the shift for leadership and ops
The cards above capture what changed in language. The bars below translate the same story into signals executives can compare against internal targets and board-ready narratives.
Benchmark bars
Before / after comparison
Indexed where noted
Manual scheduling load (index)
On-time delivery
Scheduling-related support tickets (index)
Percentages and indexes are directional composites from the engagement—your metrics should be modeled against your own baselines and seasonality.
Section 05
What the customer said
Voice of the customer
“novagentum.ai's agentic solution turned our scheduling into a strategic advantage — fewer late deliveries, fewer firefights.”