Mar 19th: Shipsy, a leading provider of end-to-end AI-native solutions for logistics, today announced AgentFleet, a fleet of purpose-built AI agents designed to work alongside logistics teams and execute operational tasks across planning, execution, customer experience, and financial operations.
AgentFleet introduces a digital workforce for logistics operations—a fleet of AI agents organized around operational roles such as customer experience, driver operations, and finance. Each agent is designed to execute specialized operational tasks across logistics workflows while working in coordination with human teams.
Despite decades of digitization, logistics operations remain deeply manual. Every day, operations teams coordinate hundreds of repetitive tasks—calling drivers stuck in traffic, chasing vendors for documents, responding to customer delivery queries, reconciling freight invoices, and escalating shipment exceptions across teams.
Logistics operations are fundamentally coordination-heavy. Customer experience teams, drivers, vendors, hubs, and finance departments must constantly exchange information to keep shipments moving. As shipment volumes grow, this coordination complexity increases—historically requiring organizations to scale operational headcount to keep pace.
Most transportation management systems and visibility platforms can identify what’s wrong in operations. But turning those insights into action still requires humans to investigate issues, coordinate stakeholders, and resolve them manually. At scale, this gap between insight and execution leads to operational cost leakage, delayed settlements, and poor customer experiences.
AgentFleet closes that gap.
With AgentFleet, enterprises deploy AI co-workers across logistics functions—agents that observe operational signals, make decisions within defined guardrails, and execute tasks across systems. Instead of spending their time firefighting operational issues, operations managers become supervisors of an AI workforce—monitoring agent activity, approving exceptions, and focusing on higher-value decisions.
This represents a shift from traditional systems of record to a system of action, where software doesn’t just surface operational problems but actively helps resolve them.
The emergence of enterprise-grade AI models, combined with increasing operational complexity and workforce constraints across logistics networks, is making it possible to automate coordination tasks that previously required large operational teams.
AgentFleet introduces AI agents aligned with real operational roles within logistics teams.
Clara — Customer Experience AI Co-worker
Nearly 40% of inbound logistics support queries are simple delivery status requests, handled today by call center teams responding to repetitive inquiries.
Clara eliminates this burden by proactively communicating delivery updates and resolving customer queries across channels that customers prefer in local languages that they understand. The co-worker can coordinate directly with drivers when needed and maintain real-time two-way communication with customers.
Early deployments show 30–40% reductions in inbound support volumes, alongside measurable improvements in customer satisfaction.
Astra — Driver Experience AI Co-worker
For enterprises managing outsourced fleets, drivers represent the last mile of operational control—and often the least connected part of the technology stack.
Astra provides drivers with real-time route guidance, delivery insights, parking intelligence, and transparent payout visibility, transforming the driver app into a tool that actively supports their work.
Early deployments show 18–20% improvements in driver productivity, with stronger engagement and lower attrition across third-party fleets.
Nexa — Finance AI Co-worker
Freight settlement is one of the most labor-intensive processes in logistics finance. Teams manually validate proof-of-delivery documents, calculate charges, match invoices, and resolve discrepancies across emails and spreadsheets.
Nexa automates this process end-to-end. The agent extracts data from freight documents—including handwritten PODs—validates charges against contracts, computes settlements, and performs four-way matching across vendor claims, execution data, GPS records, and delivery confirmations.
Organizations using Nexa achieve 20–25% faster settlement cycles, up to 50% reduction in manual workload, and significant reductions in freight billing leakage.
Vera — Dispute Resolution AI Co-worker
When financial disputes arise with carriers and vendors, operations teams often spend weeks coordinating across departments to resolve them.
Vera ingests disputes from multiple channels—including dashboards, email, and messaging platforms—collects relevant shipment and contract data, validates claims, and drives disputes to resolution.
Organizations using Vera see 20–25% faster dispute resolution cycles, reduced operational backlogs, and stronger vendor relationships.
AgentFleet operates within a centralized operational layer that continuously monitors logistics workflows and coordinates agent activity across systems. This orchestration layer enables agents to collaborate across functions—such as customer support, driver operations, and finance—to resolve operational issues end-to-end.
AgentFleet is designed to work within existing enterprise technology environments. The agents integrate with existing TMS platforms, ERPs, and third-party logistics systems, allowing enterprises to deploy AI co-workers as an augmentation layer rather than requiring a full technology replacement.
Each agent operates through a defined trigger-and-action framework, executing tasks within pre-approved guardrails covering role-based access, approval workflows, and enterprise data security policies. Human supervisors can monitor all agent activity in real time through web and mobile task views, with full auditability of actions and decisions.
Enterprises can begin with a single use case and expand across additional workflows over time. Initial deployments can scale quickly using templated rollout models that accelerate expansion across geographies.
“Supply chains are under more pressure than ever—from cost and sustainability expectations to rising customer demands,” said Soham Chokshi, Co-Founder and CEO at Shipsy.
“AgentFleet enables enterprises to augment their teams with AI co-workers that continuously observe operations, identify risks, and take action. Our vision is for every logistics team to upskill and amplify outcomes with a fleet of agents that execute at scale, learn continuously, and keep humans in control of what matters most.”
You can talk to Shipsy’s first AI-native sales executive and learn more about AgentFleet at agentfleet.shipsy.ai.
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