Know what every trip earns.Know what each pallet costs.Know what's been billed.Then act on it.
Data Semantics shows transport, warehousing and freight businesses what every job, trip and customer really earns, and puts AI agents to work on the follow-up: billing what was delivered, processing carrier invoices, answering customers and collecting cash, on the systems you already run.
For transport and fleet operators, warehousing and 3PL providers, freight forwarders and last-mile networks.
Data Semantics provides analytics, automation and AI agents for 3PL, transport, freight forwarding and courier operators. We connect contracts, jobs, trips, warehouses, invoices and payments into one view of profitability by job, customer, lane and site. AI agents then find and bill unbilled work, process carrier invoices and follow up receivables, with people approving what matters. Start with either analytics or automation.
Sales, operations, warehouses, fleet, customer service and finance each run on different systems. Every gap between them is where margin, service and cash leak.
Four operating models, one foundation: connect the data, model the business, then automate the decisions that matter. Buying and selling the goods yourself? See trading and distribution.
Warehousing and contract logistics for manufacturers, OEMs and retailers, priced per activity, pallet or trip.
Road transport and dedicated fleets moving goods for OEMs, distributors and retailers, often on long-term contracts.
Ocean, air and multimodal forwarders managing jobs across carriers, agents and borders.
High-volume parcel and last-mile networks where every failed delivery and customer call costs money.
We combine industry understanding with the technical know-how to build what you need, from analytics and automation to AI agents that act. These are the most common starting points, and the last card in each row covers everything else.
Job and customer profitability intelligence connects rates, accruals, actual costs, surcharges and billed revenue to show what each job, trip, lane, customer and contract really earns.
Shipment and service intelligence combines milestones, tracking events, PODs and commitments to show which shipments are at risk and which customers will feel it, building on the tracking you already have.
Fleet and warehouse intelligence connects trips, vehicles, fuel, telematics, labor and warehouse activity to show where capacity is used, idle or wasted.
Need something else analyzed or automated? Talk to an expert →
Billing and collections automation finds delivered work that hasn't been billed, then uses AI agents to invoice, follow up, resolve disputes and reconcile payments.
AP and document automation validates carrier, agent and subcontractor invoices against job accruals and agreed rates, and reads trade documents such as bills of lading and certificates of origin.
Customer service automation answers shipment status, delivery, rescheduling and POD questions across chat, voice and messaging, and hands complex cases to your team with full context.
Tell us where your teams lose the most time today. We’ll show you what we would fix first, on the systems you already run.
A logistics ontology is a shared model of your business: the contracts, customers, jobs, trips, vehicles, carriers, invoices and payments, how they relate, and which system each lives in. Your transport system knows the trip, your telematics knows the truck and your ERP knows the carrier invoice. The ontology knows they're the same job for the same customer.
Two workflows logistics teams often start with.
Work you've done but haven't billed is the cheapest margin you'll ever recover.
Every carrier, agent and subcontractor invoice checked against what you agreed and what was moved.
We don’t borrow results from other industries. Every logistics engagement starts by measuring today’s baseline, and success is proven against it. These are the measures we track most often.
Storage, handling and labor data brought together, so each client contract shows what it earns and what it costs.
Trade documents and carrier invoices captured with Serina, checked against job records and posted, with exceptions routed to operations.
Each is a fixed-scope engagement on your own data, measured against today’s baseline.
What every job, lane and customer really earns once carrier costs, surcharges and accruals are counted.
Business Intelligence & Analytics →AutomationDelivered work matched to invoices, missing charges billed and overdue accounts followed up by AI agents.
Zebo →AutomationCarrier, agent and subcontractor invoices matched to job accruals and agreed rates, then posted to the ERP.
Serina →Every engagement follows the same path: measure today’s baseline, connect and model the data, prove it on a real workflow, then scale.
About logistics AI
A logistics ontology is a shared model of your business: contracts, customers, jobs, trips, vehicles, carriers, invoices and payments, and how they relate, mapped to the systems where each lives. It gives every report and every AI agent the same definitions and full context, which is what makes their answers and actions trustworthy.
Profitability and billing
Job profitability intelligence connects contract rates, accruals, actual carrier and operating costs, surcharges and billed revenue, so you can see what each job, trip, lane, customer and contract really earns, not just what it billed.
Data Semantics compares delivered jobs, trips, PODs and handling activity with what has been invoiced, apply the agreed tariff for surcharges, detention and accessorials, and raise draft invoices for approval. Zebo then follows up and reconciles payment.
Yes. Serina captures carrier, agent and subcontractor invoices and matches them to job accruals and agreed rates. It also reads trade documents such as bills of lading and certificates of origin, configured to your documents and rules.
Systems and data
SAP, Oracle Fusion and EBS, Microsoft Dynamics 365 and AX and Salesforce are the most common, plus transport, warehouse, freight-forwarding, telematics and banking systems. If your data is in a system, we can usually connect it.
No. Data Semantics builds on what you run today, including your ERP, transport, warehouse and tracking systems, and Microsoft Fabric, Databricks or Snowflake if you use one. Where data needs cleaning or moving, DataPrep 360 handles it as part of the work.
Our solutions run on Microsoft Azure and can be deployed in your own tenant and preferred region, so your data stays under your control.
Getting started
Yes, and we recommend it. Common starting points are unbilled revenue, carrier invoice automation, job and customer profitability, and shipment-status customer service. Each new use case reuses the same ontology, so it goes live faster.
AI agents flag at-risk shipments and margin leaks, match invoices, draft bills, answer customers and follow up on payments within guardrails you set. Decisions such as rerouting, rate changes, credit holds and write-offs stay with accountable people, and every action is logged.
Against a baseline measured with you at the start, such as unbilled revenue, cost per invoice, margin per job or trip, on-time delivery, days sales outstanding or customer contact volume.
Unbilled jobs, carrier invoices, margin or collections. We'll show you what it looks like automated, on your own data.
