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Logistics & distribution Illustrative engagement

An ERP and a warehouse that talk to each other: robots, sensors and software on one platform

A third-party logistics company with distribution centers in the southeastern United States, a leader in its segment.

Scale
4 distribution centers, autonomous mobile robots, industrial sensors, custom ERP
Engagement
Platform build and phased warehouse deployment over 14 months

The challenge

Inventory lived in an off-the-shelf system that could not talk to the warehouse floor. Staff re-keyed data, stock counts drifted, and adding robots or sensors meant a new integration project each time.

Warehouses create data constantly: every scan, every pick, every pallet movement. Much of it never reached the system of record. Inventory lived in an off-the-shelf system that could not talk to the warehouse floor, so staff re-keyed data, stock counts drifted, and adding robots or sensors meant a new integration project each time.

We built the platform from the floor up. Scanners, scales and temperature and vibration sensors publish events over MQTT to a local broker in each building, industrial equipment such as conveyors and machine controllers speaks OPC UA, and the custom ERP, which the company owns, consumes those events to keep inventory, orders, billing and carrier integrations current. Robot fleets are orchestrated through their own APIs and shown in the same dashboards as human workflows, so a manager sees one picture of the building.

The network is designed for machines as much as people. Operational technology sits in its own segment, separate from office networks, with 802.11ax Wi-Fi tuned for fast roaming (802.11r) so scanners and robots do not drop sessions as they move. Each building has an edge server so picking and shipping continue if the internet link fails, synchronizing when it returns. A site survey with real robots on the floor set access point placement, because a robot that loses its session stops and blocks an aisle.

The deployment ran one distribution center at a time over 14 months. The first building ran the old and new systems in parallel for a month, with nightly reconciliation reports showing every difference. Once the numbers matched for a full inventory cycle, the old system became read-only. Later buildings reused the same blueprint and went live in weeks. Cycle counts were done on the cutover weekend to give the new ERP a trusted starting inventory.

Testing covered the failures that stop a warehouse. We cut the building's internet link during a busy shift and confirmed that picking, packing and label printing continued from the edge server and synchronized cleanly afterward. We replayed a day of scan events at ten times speed to size the broker. Stock levels now update in seconds instead of hours, manual re-keying is largely gone, and adding a robot or sensor is configuration rather than a project.

What our team delivered

  • A custom ERP for orders, inventory, billing and carrier integrations, built around the company’s own workflows
  • An industrial IoT layer: scanners, scales, temperature and vibration sensors publishing over MQTT, with OPC UA to conveyors and machine controllers
  • Wi-Fi designed for roaming scanners and robots (802.11ax with fast roaming, 802.11r), with a segmented network for operational technology
  • Integration with autonomous mobile robot fleets through their APIs
  • Edge servers at each building so operations continue if the internet link drops
  • Dashboards for managers and automated exception handling

Result

Stock levels updated in seconds instead of hours, manual re-keying largely eliminated, and a platform where adding a robot or sensor is configuration rather than a project. In the modeled program, the first building went live after six months as a pilot, the other three followed in sequence over the remaining eight, and the old system ran in parallel until stock counts matched for a full month. Each building's edge server kept scanning and picking during a link outage and synchronized afterward, and exceptions such as a short pick or an out-of-range temperature opened a task automatically.

Automated data entry

Bots read invoices, forms and emails, check every field, and post clean records to your books, with a person reviewing only the uncertain cases.

Automated data entryInvoices, forms and emails are picked up by three bots working in parallel. Each bot reads the document and extracts its fields one by one, a validation step checks them against business rules, low-confidence items go to a person for review, and approved records are posted to the ERP and accounting system. Manual keying shrinks as the bots take over.INCOMINGBOTS EXTRACTCHECKPOSTEDInvoices, formsand emailsBot 1Bot 2Bot 3Validaterules andconfidenceERP / ledgerauto-postedHuman reviewlow confidenceDOCUMENTS POSTEDNo typing.1,201234567890123456789Manual keyingBots

ERP development and integration

One database keeps finance, sales, inventory, purchasing and HR in sync, connects to your banks and partners, and grows with custom modules built for how you work.

ERP development and integrationFinance, sales, inventory, purchasing and HR modules share one PostgreSQL database and stay in sync. A secure API connects the ERP to e-commerce, banking and shipping partners, and a new custom module is plugged in without disturbing the rest.YOUR ERPINTEGRATIONSPostgreSQLsource of truthFinanceSalesInventoryPurchasingHRAPIsecureRESTE-commerceBankingShippingCustom modulebuilt for your process

Super Intelligence data flow

Every request is classified by sensitivity, so confidential data stays on models inside your walls while routine work can use the best frontier AI.

Super Intelligence data flowEmail, documents, phone calls, ERP and CRM records and sensor data enter a secure gateway that classifies each request by sensitivity. Sensitive requests are answered by local models inside the firewall, internal ones by a private cloud, and general ones by frontier models from leading US AI labs. Results flow back into ERP, CRM, dashboards and to people.SOURCESGATEWAYMODEL TIERSYOUR SYSTEMSEmailDocumentsPhone callsERP / CRMSensorsSecuregatewaysorts bysensitivityLocal modelsIn your firewallPrivate cloudYour own tenantFrontier modelsleading US AI labsERPCRMDashboardsPeopleSensitive: stays localInternal: private cloudGeneral: frontier model

Roaming without dropping the call

Time from leaving one access point to the first data frame on the next, split by phase. A full WPA2/WPA3‑Enterprise re-authentication repeats the 802.1X exchange; 802.11r (Fast BSS Transition) reuses cached keys, 802.11k (neighbour reports) removes the blind scan, and 802.11v (BSS transition management) lets the network steer the client. Illustrative figures.

Roaming without dropping the callStacked horizontal bars of handoff time in milliseconds. Full re-authentication 580: scan 180, authentication and association 10, 802.1X 350, four-way handshake 40. PMK caching 230. 802.11r only 200. 802.11r with k and v 40, under the 50 millisecond voice target.Handoff time by roaming method (ms)Channel scanAuth + association802.1X / EAP4-way handshake0100200300400500600ms50 ms: a voice call does not noticeFull re-authenticationno roaming aids580 msPMK caching / OKCkeys reused, still scans230 ms802.11r onlyfast transition, still scans200 ms802.11r + k + vtargeted scan, fast transition40 msIllustrative: scan 20 to 250 ms depending on channel count; EAP depends on the RADIUS round trip.

Frequently asked questions

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How do sensors and machines reach the ERP?

Scanners, scales, temperature and vibration sensors publish over MQTT, with OPC UA to conveyors and machine controllers. The custom ERP handles orders, inventory, billing and carrier integrations. Stock levels update in seconds instead of hours.

What keeps a building running if the internet fails?

Edge servers at each building keep operations going if the internet link drops. Operational technology sits on a segmented network, separate from other traffic. Wi-Fi is designed for roaming scanners and robots using 802.11ax with fast roaming (802.11r).

How are robots added?

Autonomous mobile robot fleets integrate through their APIs. Adding a robot or sensor becomes configuration rather than a new integration project, which was the earlier problem. Dashboards and automated exception handling serve managers.

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