West Chester – October 07, 2026 -- Trellist, Inc. has cut customer service call volume by 30% for a national logistics, transportation, and storage operator through a multi-phase AI engagement, delivering a six-figure net positive annual return.
AI engagement frees 30% of client's development team capacity
The veteran-owned professional services firm deployed its AI-Powered Transformation practice to redesign operational handoffs between marketing, sales, operations, and customer service teams. Trellist first unified the client's disconnected marketing, sales, and operations data into a single pipeline with real-time feeds, allowing teams to adjust performance against live data.
Development and QA workflows recover 30% of team capacity
Trellist then embedded AI directly into the development and quality assurance workflows, recovering 30% of that team's capacity for higher-value work. The firm built and organized custom MCP servers to give AI secure access to required connectors and systems, matching AI intelligence levels to specific tasks within existing infrastructure such as Salesforce and Amazon Bedrock.
AI agent resolves common customer issues in conversation
In the final phase, Trellist analyzed call-tracking data to identify why customers were calling, then built an AI agent that resolves common issues directly in conversation. The agent includes human review and operates inside the client's existing customer service workflow.
Gavin Garrison, Partner & Account Leader at Trellist, said the firm loads AI intelligence against a complex process to observe how far it can handle tasks end-to-end. Gaps that emerge show where human intervention or new system connections are needed, informing adjustments to the operational process map.
Trellist positions AI deployment as standalone practice discipline
Every Trellist engagement concludes with enablement, transferring AI capability to the client's internal team. The practice offers AI strategy, workflow modernization, custom MCP servers, AI agents, and fractional AI teams to organizations seeking operational AI deployment.