AI, data, and tech for logistics and supply chain
We help logistics and supply chain teams connect orders, inventory, freight, warehouse work, supplier follow-up, and customer promises into working systems.
Late shipments, stockouts, supplier misses, blocked orders, and ETA risk
Month-to-month implementation support, cancel anytime
Operations, supply chain, warehouse, procurement, customer service, or leadership teams
The work breaks when orders, inventory, documents, and delivery promises do not move together.
Many logistics and supply chain workflows still run through ERP screens, WMS tasks, carrier portals, supplier emails, order exports, customer messages, and spreadsheets. AI can help, but only when the source data, review rules, and handoffs are built into the workflow.
Exceptions are found too late
Late shipments, stockouts, missing documents, pick delays, supplier misses, and customer risk often surface after the team has already lost time.
Status checks depend on people
Sales, support, planners, buyers, and warehouse leads often need to ask multiple teams before they can answer what is blocked, late, available, or promised.
Reports are not operating tools
Supply chain analytics can show trends, but teams still need a daily workflow that assigns ownership, captures decisions, and closes the loop.
The output is a working operating loop, not another detached dashboard.
The build connects the order, inventory, warehouse, freight, supplier, and customer data already inside the business, then turns it into a workflow people can use in the morning review and throughout the day.
Exception reporting workflow
ERP orders, inventory balances, purchase orders, supplier confirmations, WMS holds, carrier milestones, and customer priority flags.
Exception logic, severity rules, owner routing, reason codes, source links, daily review view, and AI-assisted summaries.
A single queue showing what is late, blocked, short, missing, or at risk, with owners and next actions.
Freight booking workflow
Shipment requests, carrier emails, booking confirmations, bills of lading, customs documents, invoices, status updates, and delivery appointments.
Document extraction, booking checklist, milestone tracker, missing-document alerts, exception notes, and reviewed customer updates.
A clean shipment view showing booking status, paperwork gaps, carrier progress, and who needs to act next.
Delivery ETA workflow
Sales orders, warehouse status, stock availability, carrier milestones, route changes, customer priority, and support tickets.
ETA logic, confidence flags, change alerts, response drafts, source evidence, and a handoff back to sales or support.
A reliable answer for the customer before the second follow-up, with clear caveats when the ETA is not yet firm.
AI reads, summarizes, and routes. Operators decide.
One logistics workflow, connected each month.
We take one workflow, such as exception reporting or ETA communication, connect the source data behind it, build the system once, and add AI where it speeds the work without hiding the trail.
Map the operating workflow
Identify where orders, stock, supplier updates, warehouse tasks, freight status, documents, and customer promises start to drift.
Define the review rules
Set the exception logic, source-of-truth choices, owners, escalation paths, cutoffs, and decision cadence.
Build the working view
Ship the dashboards, internal tools, integrations, automations, and AI-assisted steps that make the workflow usable day to day.
Run it through real volume
Tune it with operations, warehouse, supplier, freight, and customer-facing teams, then move to the next workflow.
Order, stock, warehouse, supplier, freight, and customer data rarely live in one clean place.
The hard part is connecting the systems, files, controls, and ownership behind logistics decisions, then making the workflow usable by the people who have to act under time pressure.
Teams need to see where a shipment, stock number, supplier update, or customer ETA came from before they act on it.
AI can classify, summarize, and draft, but exception decisions need accountable owners and a visible audit trail.
The workflow has to fit daily standups, warehouse cutoffs, supplier follow-up, carrier updates, and customer service habits.
Practical guides for the workflows on this page.
Each guide breaks one workflow into the real situation, data, systems, AI support, human review, and a practical first implementation path.
How to Build Supply Chain Exception Reporting That Teams Actually Use
How to Fix the Warehouse Pick-Pack Handoff Before Promises Break
How to Build a Cleaner Freight Booking and Document Workflow
How to Make Supplier Scorecards and OTIF Reporting Useful
How to Build Inventory Reorder Visibility Before Stockouts Start
How to Improve Customer Delivery ETA Communication
Common questions
What logistics and supply chain workflows can Ubisar improve first?+
The best starting points are usually exception reporting, warehouse pick-pack handoffs, freight bookings and documents, supplier OTIF scorecards, inventory reorder visibility, customer delivery ETA communication, or a recurring operating review that still depends on manual spreadsheet cleanup.
Is this warehouse automation or operational implementation?+
The focus is operational implementation. Warehouse automation, analytics, and AI can help, but the value comes from connecting the order, inventory, supplier, freight, document, and review steps that teams use every day.
Where does AI actually help in logistics and supply chain workflows?+
AI is useful when it supports a specific workflow: classifying exceptions, extracting facts from freight documents, summarizing supplier and carrier updates, drafting customer ETA messages, highlighting reorder risk, and preparing reviewed commentary for operating meetings.
Start with the supply chain workflow where status gets chased the most.
Tell us where exceptions, handoffs, documents, inventory decisions, or customer ETAs still depend on manual follow-up. We'll pick the first workflow to wire together.