Booking automation
99%+Enterprise AI platform
AI Agents for Logistics That Execute the Work.
Shipflow gives enterprise logistics teams AI agents that complete booking, document processing, shipment tracking and customer workflows across email and existing systems. AI Operators follow your SOPs, verify the result and bring your team in when judgment is needed.
- Follows your SOPs
- Connected to existing systems
- Human control built in
From category to productionA practical definition
Market categoryLogistics AI agent
Understands context and can take action.
Shipflow operating modelAI Operator
Executes a governed workflow to a defined outcome.
- 01ObserveEmail, document or system event
- 02DecideSOP, context and permission boundary
- 03ActPermitted system or communication step
- 04VerifyComplete the outcome or escalate
Enterprise AI automation built specifically for global logistics
Multi-modeconnected logistics workflows
50+logistics use cases supported
Millionsof transactions handled every month
The short answer
What is an AI agent in logistics?
An AI agent in logistics is software that uses shipment information and business rules to carry out operational tasks across email, documents and connected systems. It can request missing information, update shipment records and follow up on milestones, with human review for decisions outside its authority.
Customer evidence
What do logistics AI agents achieve in practice?
Three Shipflow deployments, three different measures. Each result applies to the workflow described—not every operation at that customer.
Document comparison
97%+Less time spent on document comparison
This result applies to the deployed MBL/HBL comparison task. Results depend on workflow scope, document quality and deployment configuration.Read the case study
Track and Trace
100%Of Track & Trace automated with Shipflow
This result applies to ColliCare’s deployed Track & Trace workflow. Results depend on workflow scope, source availability and deployment configuration.Read the case studyChoose the right operating model
AI agents, copilots and RPA: what changes?
These approaches can work together, and product capabilities overlap. Compare the work each system actually completes—not just whether it is called an agent.
Agentic AI means connecting reasoning with actions across a workflow. For Shipflow, that means interpreting operational context, taking the next step and checking the result. See how agentic workflows differ from isolated task automation.
01Assist
AI copilot
Drafts, summarizes and recommends while a person remains responsible for moving the workflow forward.
Useful when a person wants help at a specific step.02Repeat
Rules-based automation / RPA
Follows a stable sequence when inputs, decisions and system behavior are predictable.
Useful for deterministic work with limited variation.03Execute
Shipflow AI Operator
Carries logistics work across systems, checks the result and escalates exceptions to your team.
Useful for repeatable work with varied inputs and operational exceptions.Illustrative booking workflow
From a booking email to a checked TMS record.
This example shows booking intake and shipment data entry—not an entire carrier booking process or a specific customer’s deployment. The same pattern applies to other logistics tasks.
- 01
Read the request
A booking email and attachment arrive. The AI Operator extracts the shipment details and identifies the customer and requested service.
- 02
Check the requirements
It checks required fields against the SOP and relevant records. Missing or conflicting details become a clarification request or a task for your team.
- 03
Prepare the system update
It maps the validated information to the shipment record in the TMS. Any action requiring approval waits for the responsible person.
- 04
Execute and confirm
After required approvals, it writes the data through the agreed system connection and checks that the intended record was created or updated.
- 05
Handle the exception
If a system update fails or a decision exceeds its authority, it gives your team the shipment context, actions taken and unresolved issue.
- 06
Measure the outcome
Track completed records, unresolved cases, remaining human handling time and corrections. A prepared booking is not a confirmed carrier booking.
50+ logistics use cases
Which logistics workflows can AI agents automate?
These eight workflows are common starting points across Shipflow customers. Explore the inputs, actions and outcomes to find the right fit for your team.
01
Quotation automation
Handle quotation inquiries 24/7—calculate rates from your data and deliver accurate, up-to-date responses in seconds.
Explore workflow02
Booking automation
Read booking emails and forms, extract and validate shipment details, and create bookings directly in your TMS.
Explore workflow03
Document automation
Process logistics documents, extract and validate shipment data, compare related files and enter approved information into your TMS.
Explore workflow04
Tender automation
Automate customer tenders and supply tenders—prepare customer responses, compare carrier bids and manage approved rates.
Explore workflow05
Track and Trace
Run configurable shipment checks across pre-pickup, pickup, in-transit and delivery—then sync confirmed milestones to your TMS and escalate exceptions.
Explore workflow06
Invoice processing
Capture carrier and vendor invoices, match charges against shipment records and expected costs, post eligible invoices and route discrepancies for review.
Explore workflow07
Carrier sourcing and coordination
When a quote arrives, shortlist carriers and collect rates. Once a carrier is booked, chase shipment status and sync the updates to your TMS.
Explore workflow08
Exception management
Detect shipment exceptions, assemble the operational context, coordinate the next action across teams, carriers and customers, and escalate decisions under your rules.
Explore workflowBuilt around the operation
One execution model. Different logistics contexts.
Forwarders, carriers, brokerages, warehouses and parcel operators have different operating needs. Explore the workflows relevant to your team and transport modes.
Modes
Individual modes and connected legs
Logistics organizations
Built for the team doing the work
Human control
Autonomy is set at the action level.
Reading a request, preparing a response, updating a record and sending an external commitment are separate permissions. Your team decides the appropriate boundary for each action.
Explore security and governance See how your team manages AI OperatorsConnected execution
Work through the systems your operation already uses.
Keep your existing systems of record. Shipflow connects the inboxes, documents and applications involved in the workflow, including internally built systems. The connection method and available actions depend on your environment.
TMS & ERP
Shipment and transportation records
Requests, attachments and replies
CRM
Customer and opportunity context
Market rates
Pricing inputs and benchmarks
Internal systems
Proprietary tools and portals
Enterprise evaluation
How to choose AI agents for your logistics operation.
Give operations, IT and procurement the same test cases. Compare a complete workflow, its exceptions and its cost—not just a polished demo.
Can it complete your actual workflow?
Use a representative request from one team, including an incomplete or revised version. Ask to see the result in the destination system—not only an extracted field or a drafted reply.
Define the booking outcomeCan it work with your TMS?
Identify the records it must read, fields it may update and how it confirms success. For CargoWise, review the eAdaptor read/write workflow, required access and duplicate-handling tests.
Review CargoWise integrationWhat happens when something goes wrong?
Test a conflicting instruction, a missing approval and an interrupted system update. Check who receives the case, what context they see and whether an uncertain action is reconciled before a retry.
Review security and human controlDoes the business case include the remaining work?
Compare handling time, eligible volume, completion and corrections for the same scope. Include human review and operating costs. Shipflow’s recurring platform fee is shaped by workflow complexity and volume.
Understand pricing and ROIAlready have TMS rules or other automation? Keep the steps that work. Evaluate Shipflow for the remaining email, document and cross-system handoffs; a stable, fully automated process may not need an AI agent.
Enterprise deployment
Put the workflow in production—not just the model.
Most Shipflow enterprise deployments move from workflow discovery to production in one to three months. Timing depends on the workflow, system access, data, security review and internal validation.
Explore the enterprise deployment process- 01
Choose a measurable workflow
Start with frequent work that has recognizable inputs, a clear definition of completion and a known exception owner.
- 02
Map the operating boundary
Define the SOP, systems, decisions, permitted actions, approvals and escalation paths that govern execution.
- 03
Connect and validate
Test representative normal cases, exceptions and system responses with the people who own the operation.
- 04
Deploy and measure
Move the agreed workflow into production, monitor outcomes and expand only after the operating boundary is proven.
Operational guidance
Design the workflow before deciding the autonomy.
Explore guidance for choosing, governing and scaling AI-agent workflows. For the wider industry picture, see eight logistics companies using AI and how their reported deployments differ in scope.
Questions, answered
What logistics leaders need to know about AI agents.
What is an AI agent in logistics?+
An AI agent uses shipment and customer context to act across email, documents, TMS platforms and other connected tools. It works within its system permissions and verifies the result or escalates to a person.
How is a Shipflow AI Operator different from an AI agent?+
AI agent is the broad category. A Shipflow AI Operator applies that technology to a complete logistics workflow, with SOPs, access controls, approval points and a clear definition of completed work.
What is agentic AI in logistics?+
Agentic AI in logistics connects reasoning with action across systems. It continues until the work is verified or needs human judgment, following SOPs, access controls and exception-handling rules.
Which logistics workflows can AI agents automate?+
Common starting points include quotation, booking, document processing, customer and supply tendering, Track and Trace, invoice processing, carrier sourcing and coordination, and exception management. Shipflow supports more than 50 logistics use cases across Ocean, Air and Road, with the exact scope configured for each operation.
Can logistics AI agents follow our existing SOPs?+
Yes. Shipflow AI Operators are configured around existing workflow steps, decision rules, system permissions, approval requirements and escalation logic. Different SOPs can be managed at company, office and team levels where operating requirements differ.
Do AI agents replace our TMS or other core systems?+
No. Shipflow adds a controlled execution layer across the systems the operation already uses, including TMS, ERP, email, CRM, carrier portals, market-rate sources and internal systems. The available connection method and permitted actions are confirmed for each workflow.
How do teams control Shipflow AI Operators?+
Teams define whether an AI Operator may observe, prepare, execute or escalate each action. Shipflow dashboards provide visibility into workflow status, context, actions, approvals, exceptions and outcomes so authorized users can monitor and manage the deployed work.
How do we measure the value of logistics AI agents?+
Compare human handling time, completed workflows, cycle time and errors before and after deployment for the same scope. Report how many incoming cases are eligible and how many finish without human intervention. Include review and later corrections; field accuracy and touchless completion are different measures.
When should an AI agent hand work back to a person?+
An AI agent should hand work back when information conflicts, a required approval is missing, a system action cannot be confirmed or a decision falls outside its authority. Your team sets the escalation rules. The handoff should include the shipment context, actions already taken and the decision still needed.
How long does deployment take?+
Most enterprise deployments move from workflow discovery to production in one to three months. Timing depends on workflow complexity, system access, data availability, security review and how quickly internal stakeholders can validate the SOP. Shipflow can move faster when the scope and required access are ready.
Start with one workflow
Turn repeatable logistics work into a controlled AI Operator.
Start with a free 15-minute AI consultation. Bring one workflow, the systems involved and your approximate volume. We will discuss the fit, success measures and a practical first deployment.
Discuss enterprise AI automation