How zeb Implemented a Secure, Multi-Agent AI System for TranscendTrail Logistics

Challenge: Manual Support Workflows and Fragmented Knowledge

Our client’s operations relied heavily on manual processes across both customer-facing support and internal operations.

All customer queries such as shipment tracking and logistics inquiries required human agent involvement. Support teams manually handled triage, follow-ups, and escalations, leading to slower response times and limited scalability.

For internal teams, operational workflows were fragmented across multiple systems and knowledge sources. Finding answers for their issues across multiple sources are inefficient and time-consuming.

Solution: Secure Multi-Agent AI Platform with Channel-Specific Experiences

zeb implemented a secure, multi-agent AI platform with two distinct conversational experiences:

• A customer-facing HubSpot chatbot: for shipment and support inquiries
• An internal Slack-based AI assistant: for operational and administrative workflows

Both experiences share a common knowledge foundation while operating with independent workflows, controls, and escalation logic appropriate to each audience.

The platform leverages AI-driven processing, automated knowledge retrieval, and intelligent routing to handle most interactions autonomously while escalating to human agents only when required.

AI-Driven Support Orchestration

The solution enables intelligent request handling through a centralized orchestration layer that routes user queries to the appropriate AI capabilities such as knowledge lookup, reporting, web-based information retrieval, or ticket creation.

HubSpot bot escalates differently by tier: Growth customers get automated tickets, while Premium/Pro users receive live agent transfers during business hours with no queues.

Internal teams use the Slack-based assistant to generate reports, track trends, manage access, and get ticket insights using natural language commands.

Multi-Agent Security, Governance, and Responsible AI

zeb’s multi-agent platform enforces strict security: Guardrails include tiered escalations, single-tool-per-request, and safe fallbacks.

Responsible AI features AWS Strands filters, upon requests live agent routing is handled during business hours, and monitoring hallucinations, PII protection, and continuous improvement.

Deployment and Scalability

The solution is deployed on AWS using scalable container-based services. This architecture enables the client to scale support operations efficiently while maintaining cost control, performance reliability, and operational visibility.

Benefits: Operational Intelligence and Secure Automation

• Unified AI across channels: Consistent intent handling and automation across customer and internal workflows.
• Faster resolution with controlled escalation: AI handles the majority of queries instantly, reducing response times while ensuring premium customers receive timely human support.
• Actionable operational visibility: Built-in analytics provide insights into customer behavior, support trends, and system performance.

Conclusion

By partnering with zeb, TranscendTrail Logistics implemented a secure, multi-agent AI system that modernized customer support and internal operations without disrupting existing workflows. The solution delivered measurable efficiency gains, improved customer responsiveness, and governed automation aligned with enterprise security standards.

This case study demonstrates how logistics organizations can apply agentic AI to real-world operations while maintaining control, trust, and scalability.

Connect with zeb to build a governed multi-agent AI platform tailored to your enterprise workflows.