Tell us what's broken.
Tell us which logistics data processes consume the most manual team time. We'll map the automation opportunity and give you a fixed cost.
RPA in Logistics Services
RPA in Logistics
Logistics operations depend on data moving accurately and quickly between carriers, customers, warehouses, and internal systems. Shipment booking, tracking status updates, customs documentation, carrier invoice reconciliation, and delivery exception handling, these are structured, rule-based workflows that consume significant operations team time.
We build robotic process automation systems that handle these workflows automatically, so your logistics operations team focuses on exception management, carrier relationships, and customer service rather than data re-entry between systems.
Shipment booking, tracking updates, and delivery confirmation automation
Carrier invoice reconciliation against contracted rates, catch billing errors automatically
Customs documentation generation and compliance check automation
Integration with TMS, WMS, ERP, and carrier APIs (FedEx, UPS, DHL, freight forwarders)
Bring the problem, the current workflow, or the existing code. We reply with a practical next step within one business day.
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The brief
Start with what is not working.
Good software decisions begin with the constraint, not a list of features or a preferred technology.
01
Operations team spending hours per day re-entering shipment data between your TMS and carrier systems?
02
Carrier invoice reconciliation taking days each month because someone has to compare line by line?
Plain answer
RaftLabs builds robotic process automation for logistics operators, automating shipment booking, real-time tracking sync, carrier invoice reconciliation, customs documentation, and delivery exception workflows. Logistics RPA connects TMS, WMS, ERP, and carrier APIs so data flows without manual re-entry between systems. A first automated workflow is delivered at a fixed cost, then expands across more carriers and processes.
What to remember
- RaftLabs automates shipment booking, tracking status updates, carrier invoice reconciliation, customs documentation, and delivery exception workflows for logistics businesses.
- Logistics RPA integrates with TMS, WMS, ERP, and carrier APIs including FedEx, UPS, and DHL so data flows without manual re-entry between systems.
- Customs documentation generation, compliance flagging, and multi-carrier integration are all supported within the same automation layer.
Logistics data moves constantly. Manual re-entry slows it down and creates errors.
A tracking status that has to be pulled from a carrier portal and re-entered in your TMS three times a day is a task a bot can do every 15 minutes with no errors. A carrier invoice that takes two days of reconciliation because someone has to compare it line by line against contracted rates is a task automation can complete in minutes and flag only the discrepancies.
Adoption concentrates in operations-heavy sectors like logistics, where structured, high-volume data processing is a direct fit for rule-based bots. Carrier invoice reconciliation is often the first process teams automate because the overbilling it recovers pays for the build.
Logistics RPA doesn't make judgment calls. It handles the structured data processing that surrounds them.
Capabilities
Logistics processes we automate
Shipment booking automation
Automated shipment booking across multiple carriers: bots receive requests from your TMS, select the carrier by your routing rules, and return tracking numbers, labels, and delivery dates within seconds. Booking errors are classified and routed to a review queue, with a full audit trail of carrier, reason, and rate.
Tracking status synchronisation
Automated tracking status pulls from carrier APIs on a defined schedule, pushed to your TMS, WMS, and customer-facing portals. Bots detect delivery failures, delays, and address issues and trigger exception workflows, so tracking data stays current without staff checking portals manually.
Carrier invoice reconciliation
Automated three-way match of carrier invoice, contracted rate card, and shipment data by service level, zone, and weight break. Incorrect accessorials, wrong zones, duplicates, and charges on unknown shipments are flagged while clean invoices approve automatically, recovering overbilled freight spend.
Customs documentation generation
Automated generation of customs declarations, commercial invoices, packing lists, and certificates of origin from your order and product systems, with HS codes, values, and origin populated per destination country. Complex or restricted shipments are flagged for compliance review.
Delivery exception handling
Automated detection and handling of failed deliveries, address corrections, customs holds, and damage notifications. Bots classify each exception from carrier tracking, trigger the right response, from customer notification to re-delivery or return, and update the relevant systems automatically for standard types.
Warehouse and inventory data sync
Automated synchronisation between WMS, TMS, and ERP: inbound receipts, inventory availability, outbound pick and pack, and despatch notifications, keeping systems aligned without manual reconciliation. For 3PLs, automated client reporting is generated from WMS data.
Deterministic bots and document intelligence do different jobs
Not every logistics document is structured. Carrier APIs and EDI feeds are. An EDI 214 status message or an EDI 210 freight invoice arrives in a fixed layout, so a deterministic bot parses it the same way every time. Scanned bills of lading, emailed rate confirmations, and customs paperwork are not. Those need intelligent document processing: OCR plus a model that reads each field wherever it sits on the page, with a confidence threshold that routes low-confidence extractions to a person.
We build both, and we are explicit about which one each document type gets. A deterministic bot on unstructured input fails silently. A model on a clean EDI feed is wasted cost and a new place for errors to hide.
Carrier-portal automation is fragile by design
When a carrier has no API, the only way in is the web portal, and a bot that logs in and reads the screen breaks the day the carrier changes its layout. We treat portal scraping as a fallback, not a foundation: API first, EDI second, portal automation last, each carrier behind a monitored abstraction layer. A broken selector raises an alert instead of pushing stale tracking to your customers. Because every carrier sits behind the same interface, a portal that gains an API later is a swap, not a rebuild.
Process
How we build logistics RPA
Carrier integration design
We design the integration architecture for your specific carrier mix: API integrations for carriers with modern developer programmes, UI automation for portal-only carriers, and EDI for freight partners. A unified abstraction layer means adding a new carrier doesn't require rebuilding the automation.
Business rules configuration
We document your carrier selection rules, routing logic, rate card structures, escalation paths, and compliance requirements by lane during scoping, then encode them directly, not a generic automation your team then has to configure around.
Exception handling and escalation
We design exception handling into every automation: the bot logs each exception with context, a carrier API error, an unparseable tracking status, an unknown charge category, and escalates to the right team member. Automation handles the standard cases; your team handles the genuine exceptions.
Performance and accuracy monitoring
Automation dashboards showing throughput, error rates, exception rates, and processing time per workflow, with alerting when error rates rise or a process falls behind. Carrier reconciliation reporting tracks overbilling recovered over time, giving operations visibility into automation performance.
What clients say
What clients say
Three-year average engagement. Founders and operators describing the work in their own words. No marketing varnish.
I definitely recommend RaftLabs, especially to solo founders like me. Their clear communication and detailed discussions have always helped me make better decisions.
Gil Nugraha
Founder at UrShipper
The closest work we can point to
Our nearest reference is UrShipper, a multi-carrier shipping platform we built with live integrations to FedEx, DHL, UPS, Aramex, and Shippo behind one interface. That project was a product build, not a pure RPA engagement, but it rests on the same core skill logistics automation needs: talking to several carriers at once and keeping shipment data in sync without manual re-entry. UrShipper was the founder's fifth attempt after four previous vendors failed.
Proof
Carrier-integration work
- 01
Multi-carrier shipping platform across 70+ countries
- shipments processed in first year
- 2k+
- customers migrated with zero disruption
- 200+
- 02
AldiFest processed 5,000 receipts and signed up 2,000 shoppers in its first week
AldiFest signed up 2,000+ shoppers and processed 5,000 receipts in week one. The campaign team also reported 2x purchase frequency and 25% higher average purchase value; the public case record does not retain the measurement method.- shopper signups in the first week
- 2,000+
- receipts processed in the first week
- 5,000
- from scoped campaign to delivery
- 14 weeks
- 03
City Break Apartments grows self check-ins 7x and direct revenue 25% with branded booking platform
We built a branded booking website with RMS Cloud integration and a Bluetooth keyless mobile app for City Break Apartments in Dublin, activating 250 Omnitec locks already installed, cutting 20+ staff hours per week, and growing self check-ins from fewer than 10 to 72+ weekly.- Weekly self check-ins via mobile app
- 72+
- Active users on the new website within 2 months of rollout
- 580+
- Growth in self check-ins after app launch
- 7x
What it costs
Every project starts at $10000.
The first phase automates one data flow: booking, tracking updates, or invoice reconciliation.
Starting investment
Starts at $10000
One logistics data flow automated across carriers, customers, and internal systems. After a 30-minute call, you get a written build, buy, repair, or wait recommendation plus first-phase direction. Free, whether or not you build with us.
The first decision is not what to build.
It is whether software is the right answer at all. We use four possible recommendations before discussing a development scope.
- 01
Buy
Choose a maintained product when it handles the core workflow and the remaining gaps can be solved with configuration, a connector, or a small process change. Paying for software you do not have to maintain is often the better trade.
- 02
Repair
Keep the existing product when users still get value from it and the code can be understood safely. Start with evidence: where the code lives, how the data is organized, what is tested, which outside services it depends on, who can access what, and how updates go live.
- 03
Build
Own the system when the back-office process shapes margin, customer experience, speed, or a product customers pay for. Start with one complete path and the system connections that path cannot work without.
- 04
Wait
Do not turn a changing policy into permanent software. Stabilise the rules, name the workflow owner, and measure the cost of the current process before paying for a product.
Not sure which path is yours? Bring it to a 30-minute call. Leave with the answer in writing.
Work with us
Logistics operations that scale without proportional headcount
Automate the structured data processing. Your team handles exceptions and relationships.
- Scope and cost agreed before work starts. No surprises. No obligation.
- Working prototype within 3 weeks of kickoff.
- Pay by milestone. You see progress before each invoice.
- 60-day post-launch warranty. Bug fixes, UI tweaks, and deployment support. No retainer.
- All conversations are NDA-protected.
Common questions
The best RPA candidates in logistics are high-volume, rule-based data processes: (1) Shipment booking, bots create shipment records in your TMS, submit booking requests to carrier APIs, and return tracking numbers without staff having to log into carrier portals. (2) Tracking status updates, bots pull tracking status from carrier APIs on a schedule and update your TMS, WMS, and customer notification systems. (3) Carrier invoice reconciliation, bots compare carrier invoices against contracted rates and shipment records, flagging billing errors for accounts payable review. (4) Customs documentation, bots generate customs declarations, commercial invoices, and packing lists from shipment data. (5) Delivery exception handling, bots detect failed deliveries, trigger customer notification workflows, and create re-delivery or return-to-sender tasks based on exception type. (6) POD collection, bots retrieve proof of delivery documents from carrier portals and attach them to shipment records.
Integration depends on what each carrier exposes. For major carriers (FedEx, UPS, DHL, USPS), we integrate via their published APIs, booking, tracking, label generation, and rate queries are available programmatically. For carriers or freight forwarders without modern APIs, we use UI automation (bots interact with web portals as a user would) or EDI integration where the carrier supports it. For your internal systems (TMS, WMS, ERP), we integrate via API where available or database integration for on-premise systems. Multi-carrier environments, common in 3PL and freight forwarding, are handled with carrier-specific adapters behind a unified automation layer.
Yes, for standard customs documentation scenarios. Bots generate customs declarations, commercial invoices, and packing lists by extracting data from your shipment records, product descriptions, HS codes, values, quantities, shipper/consignee details, and country-of-origin information. For straightforward B2B commercial shipments, the documentation is largely template-based and fully automatable. For complex shipments (restricted commodities, special regimes, multi-origin consignments), the bot generates the draft and flags the shipment for compliance review before submission. We design the automation around your shipment profile and the specific countries and commodities you work with.
RPA fits best for systems with no clean API: the bot logs into the TMS and portals to assemble spot quotes. Use direct API for stable, documented APIs; OCR and AI for quotes arriving as PDFs or free-text email. Where no clean API exists, the bot works screen-based with rule-based keying. Estimate monthly saving as manual minutes per quote minus automated minutes, times quotes per month, times loaded hourly cost. Quote turnaround drives win rate, not just cost.
The mistake called out explicitly: ignoring exception handling, so the team stops trusting the bot after the first odd request. The automation-before-automation rule: fix the pricing rules and the process before building the bot; prove one high-volume case first. Trying to automate every quote type at once instead of proving one case is the classic failure. Measure quote time, win rate, hours reclaimed: not bots built. Leaving the bot as an island instead of a reusable platform is the long-term trap.
A first automated workflow covers one process, such as multi-carrier tracking sync or carrier invoice reconciliation. The full programme covering booking, tracking, reconciliation, and exception handling across multiple carriers and systems grows as you add processes. Cost depends on the number of carriers and systems to integrate, the complexity of the business rules, and the volume of exception handling logic required. We scope every project before pricing it.