Connect shipment, fleet, warehouse, document and financial data. Predict delays. Detect exceptions. Coordinate approved actions across your logistics network with Mimasa AI.
Mimasa brings AI agents, logistics automation and real-time decision intelligence into the systems your teams already use. It applies AI in transportation without forcing teams to replace their operational platforms. Operations leaders get earlier warnings. Teams get clear next steps. Every important action can remain governed and auditable.
Cloud, private-cloud/VPC and on-premise deployment | Human approvals | Role-based access | Auditable workflows
A shipment may touch a TMS, carrier portal, warehouse system, GPS feed, spreadsheet, email thread and customer account before it arrives.
Each system holds part of the answer. Operations teams still spend hours collecting updates, checking milestones and deciding whom to contact. By the time a delay appears in a report, the service commitment may already be at risk.
Mimasa AI creates a governed intelligence and automation layer across this fragmented environment. It helps teams understand what is happening, why it is happening and what approved action should follow.
AI in logistics uses operational data, machine learning and AI agents to help transport teams predict risks, investigate performance and automate repetitive work. In practical terms, artificial intelligence in logistics connects signals that people would otherwise have to assemble manually.
Useful AI does more than generate a dashboard. It connects events across shipments, routes, warehouses, documents and costs. It identifies the situations that require attention. It then recommends or executes the next permitted step through a controlled workflow.
Mimasa AI works with existing logistics systems. It provides AI for logistics as an intelligence and orchestration layer, without requiring an organization to discard its TMS, WMS, ERP or telematics platform.
Bring together data from databases, APIs, TMS and WMS platforms, ERP applications, GPS or telematics feeds, carrier updates, spreadsheets, email and documents.
Map shipment identifiers, routes, milestones, carriers, customers and service levels. Validate missing, inconsistent or duplicate records before analysis.
Use logistics analytics and natural-language questions to explore performance. Identify delayed milestones, dwell-time anomalies, cost variances and SLA risks.
Apply predictive analytics in logistics to estimate arrival risk, likely delay or maintenance needs when sufficient historical and live data is available.
Send consequential recommendations to the right person. Apply permissions, confidence thresholds and human-in-the-loop review.
Create tasks, send approved alerts, generate reports or update connected systems. Maintain an execution trail showing what happened and why.
Each capability starts from data your teams already produce and ends with an owner, an approval and a recorded action.
Create a connected view of shipment milestones across modes, carriers and locations. Detect missing updates, prolonged dwell, customs holds, route deviations and delivery risks. Route each exception to a defined owner instead of leaving it inside a dashboard.
Estimate arrival risk using available shipment history, route performance, carrier behavior and live signals. Compare planned and predicted arrival times. Alert teams when a threshold changes or an SLA becomes vulnerable.
Predictions depend on the quality and availability of your data. Mimasa does not promise a universal accuracy rate.
Ask operational questions in natural language. Compare lanes, carriers, customers, facilities and shipment types. Turn the findings into dashboards, scheduled reports, Excel outputs or presentation-ready reviews.
See how freight and transportation analytics works
This transportation analytics software capability helps planners move from static reporting to faster investigation.
Extract freight invoices and connect them with shipment records, contracts or approved rate cards. Flag duplicate invoices, unexpected surcharges, missing references and charge variances. Route exceptions for review before posting or payment.
Extract and validate data from bills of lading, proof-of-delivery records, invoices, packing lists and other operational documents. Associate documents with the relevant shipment. Route incomplete or inconsistent records to a person for verification.
Analyse connected vehicle, trip, fuel and maintenance data. Compare utilization, route performance, fuel variance, breakdown history and maintenance patterns. Predictive maintenance requires adequate vehicle and service history.
Fleet Performance Intelligence
Mimasa provides an intelligence layer over telematics data. It is not a GPS device or fleet-tracking system.
Bring receiving, put-away, picking, packing, staging and dispatch information into a shared operational view. Find throughput constraints and delayed handoffs. Trigger alerts or tasks when agreed thresholds are breached.
Combine current operational views with exception queues, AI-generated summaries, investigations and approved workflows. Give leadership the network view while planners drill into the shipment, route or event behind every metric.
Mimasa combines AI agents with deterministic workflow steps. Agents interpret context, analyse evidence and prepare recommendations. Workflows enforce rules, permissions, approvals and system actions.
This makes the platform relevant to teams evaluating AI logistics software for controlled logistics process automation, with people in control of consequential decisions.
Explore enterprise AI agents or agentic workflow automation.
Monitor active shipments, investigate exceptions and coordinate next steps.
Bring multimodal milestones, documentation and customer commitments into a shared view.
Analyse utilization, route performance, fuel variance and maintenance history from connected sources.
Identify receiving, picking, staging and dispatch bottlenecks.
Validate freight invoices, analyse logistics costs and reconcile charge exceptions.
Understand shipment status, SLA risk and the evidence behind each update.
Review service, cost and network performance without waiting for another manual report.
Mimasa is not another system of record. It connects the data and work already spread across the organization.
Available integrations depend on the customer environment and implementation scope. Each connection is configured, permissioned and tested.
See AI data extraction for documents, email and unstructured freight records.
Start with one measurable workflow rather than attempting to automate the complete network at once. This approach makes logistics automation easier to govern and measure.
A freight organization can combine shipment information, predict ETA risk, surface exceptions and monitor service-level performance. Operations teams can ask questions about delayed shipments, routes and customer commitments while workflows assign follow-up actions.
Mimasa can help logistics organizations monitor these areas. They are measurement areas, not guaranteed outcomes. Baselines and targets must be defined for each implementation.
Logistics workflows can involve customer data, shipment locations, commercial rates and operational decisions. Teams decide which actions agents may recommend, prepare or execute.
Common questions about AI in logistics and transportation automation with Mimasa AI.
Purpose-built logistics agents with approved data and tools.
Rules, permissions, approvals and connected system actions.
AI data extraction from freight documents, invoices and email.
Data governance and collaboration across logistics teams.
Operational dashboards for shipments, lanes and carriers.
Insights and reporting for service, cost and network reviews.
Start with one high-impact workflow. Connect the relevant data, measure the current baseline and show how Mimasa AI can help your team detect risks and act sooner.
