Case Study: How a $30M Logistics Company Cut Operational Costs 60% in 8 Weeks

Client Profile: A $30M/yr regional logistics and freight forwarding company.
The Problem: The operations team was drowning in unstructured data. Dispatchers were manually reading hundreds of emails daily, extracting load details, cross-referencing driver availability, and manually entering data into a legacy ERP. The error rate was 8%, leading to missed pickups and SLA penalties.

The Vyaktra Solution: Autonomous Triage

We didn't replace their ERP; we built an intelligent orchestration layer in front of it. We deployed a three-agent system designed to handle the entire inbound pipeline:

1. The Extraction Agent: Monitored the central dispatch inbox. Using advanced NLP, it read inbound emails and PDFs, extracting pickup locations, weight, dimensions, and delivery windows with 99.8% accuracy.
2. The Routing Agent: Queried the fleet management API to check current driver locations, hours-of-service limits, and vehicle capacities, calculating the most profitable route assignment.
3. The Execution Agent: Drafted the dispatch order in the ERP and sent a confirmation email to the client.

Handling the Edge Cases

If an email contained ambiguous load details, or if no driver was available within the SLA window, the system did not guess. It instantly routed the ticket to a human dispatcher's "Exception Queue" with a summary of the problem and a drafted response asking the client for clarification.

"Vyaktra didn't just build software. They mapped our entire operational flow and eliminated blind spots we didn't know we had. Our dispatchers are now managing exceptions, not doing data entry."

The Business Outcome

Within 8 weeks of deployment, the system was handling 85% of all inbound load requests autonomously. The company absorbed a 30% increase in seasonal volume without hiring additional dispatch staff, effectively expanding their profit margins by 60% on new revenue.