Logistics & Supply Chain
Software engineering for Warehouse Management
A warehouse lives or dies on inventory accuracy and throughput, and the hard part is almost never the screens: it is integrating the physical hardware, keeping stock real-time under load, and surviving a peak that does not care how good the demo looked. We build WMS around how pickers, packers and rugged scanners actually move through the four walls, not around an idealised process nobody follows on the floor.
Why the domain matters
Warehouse management is where supply-chain software stops being about lorries and networks and starts being about the four walls of a specific building: the racking, the aisles, the pickers on their feet, the rugged handhelds in their hands, and the stock that has to be exactly where the system says it is. It is a discipline of its own, distinct from transport and wider supply-chain planning, because the constraints are physical and immediate. A picking route that adds fifty metres per order, a scan that fails intermittently on a cold-store handheld, a stock count that drifts a few units out of true: none of these are abstractions. They are throughput lost, orders shipped short, and a peak week that turns into a firefight. Warehouse management software succeeds or fails on how well it respects that physical reality.
The two numbers that matter almost everywhere are inventory accuracy and throughput, and they pull against each other. Accuracy is the promise that the quantity the system claims is on the shelf is genuinely there, so that orders can be committed, picked and shipped without nasty surprises. Throughput is how many order lines you can pick, pack and dispatch per hour, which is what actually determines whether the building can cope with demand. Push throughput too hard with sloppy processes and accuracy decays; chase perfect accuracy with heavy counting and verification and throughput collapses. A good WMS holds both: accurate stock maintained continuously through disciplined cycle counting and clean scanning, and high throughput through sensible slotting, efficient picking strategies and short, well-planned travel. The whole design is a negotiation between those two forces.
We are a senior-led team and we operate what we build, so we start on the floor rather than in the product backlog. The recurring failure mode in warehouse software is a WMS designed around a tidy process model that the actual operation does not follow, running on hardware nobody stress-tested, that falls over the first time volume spikes. We would rather walk the aisles, watch a pick round, see where the scans fail and where the paper workarounds have quietly crept back in, and build for that. The interface is the easy part. The hard part is integrating the physical hardware (scanners, conveyors, AS/RS, pick-to-light), keeping stock accurate and real-time while dozens of people and machines move it simultaneously, and holding throughput when the building is under the most pressure it will ever see.
The challenges in warehouse management
Inventory accuracy that survives continuous movement
Stock is being picked, put away, moved, returned and adjusted by many people and machines at once, and every one of those events is a chance for the recorded quantity to drift from the physical one. Once accuracy decays, every downstream promise (availability, allocation, picking), is built on sand, and orders ship short. Holding accuracy is not a one-off count; it is disciplined scanning, tight transactional design so no movement goes unrecorded, and cycle counting that finds and corrects drift continuously rather than waiting for a disruptive annual stocktake.
Throughput under peak, not on an average Tuesday
A WMS that copes comfortably with normal volume can still collapse during a peak (Black Friday, a promotion, a seasonal surge), when order lines per hour multiply and the whole operation runs hot. Peak is where picking strategy, slotting, hardware and the software all get stress-tested at once, and where the paper fallbacks come out if the system stalls. We design and load-test for the worst week of the year, because that is the week the business actually needs the system to hold, and an average-case design is a promise you cannot keep in December.
Integrating physical warehouse hardware
The distinctive difficulty of warehouse software is that it drives and listens to physical equipment: rugged handheld scanners and wearables, conveyors and sortation, automated storage and retrieval systems, pick-to-light and put-to-light, weighing and dimensioning. Each has its own interface, timing and failure behaviour, and none forgives a naive integration. A conveyor does not wait for a slow database write; a scanner in a chiller behaves differently from one on a warm mezzanine. Getting this right is real embedded-adjacent engineering, and underestimating it is the classic way a WMS project ships late and half-connected to the floor.
Picking strategy is the throughput engine
How you pick (discrete order picking, batch, cluster, wave, zone, or pick-and-pass across zones), is the single biggest lever on throughput, and the right choice depends on order profile, building layout and volume, not on fashion. A strategy that suits small, single-line web orders is wrong for large multi-line wholesale ones, and a building may need several running at once. Get the strategy and the slotting behind it right and pickers walk less and pick more; get it wrong and you are paying for travel time on every order, all day, forever.
Slotting that is never finished
Where each SKU lives in the building determines how far pickers walk and how congested the hot aisles get. Good slotting puts fast movers in the most accessible, ergonomic locations and groups items that are ordered together, but demand shifts constantly, so slotting is a living optimisation, not a one-time layout. A WMS has to support re-slotting without disrupting live operations, and the data to drive it (velocity, affinity, seasonality), has to be captured and trusted, or the building slowly de-optimises around a plan that stopped being true months ago.
3PL multi-client complexity
A third-party logistics operation runs many clients under one roof, each with their own SKUs, service levels, billing rules, branding on the paperwork and often their own required integrations. The WMS has to keep inventory and activity cleanly segregated per client, bill accurately for storage and handling, and honour each client’s rules without turning the building into a maze of exceptions. Multi-client billing and segregation are a whole layer of complexity a single-owner warehouse never has to face, and doing it sloppily either loses the 3PL money or loses it clients.
What we build for warehouse management
The systems this sector most often needs, built by engineers who understand the domain, not just the code.
Core WMS: receiving to dispatch
The operational spine of the building, goods-in and put-away, location and inventory management, allocation, picking, packing, despatch and returns, built as a real-time transactional system where every physical movement is scanned and recorded. We design the transaction model so stock cannot silently drift, the location logic to reflect how the racking is genuinely used, and the workflow around how the floor actually operates, because the core WMS is the thing the whole operation leans on every shift and it has to be dependable before it is clever.
Picking strategies and wave planning
Picking engines that support the strategy the operation actually needs (discrete, batch, cluster, zone and wave or pick-and-pass), with wave planning that releases work in a way that balances the floor, feeds packing steadily and hits despatch cut-offs. We treat the choice of strategy as an engineering and operations decision driven by order profile and layout, and we build so it can be tuned and combined, because the picking method is the largest single determinant of how much the building can ship.
Scanning, RFID and rugged device support
Barcode and, where it genuinely earns its place, RFID capture built for the reality of rugged handhelds, wearables and vehicle-mount terminals, intermittent connectivity, gloves and cold stores, scans that must be fast and forgiving. We design the on-device workflow for people moving quickly under pressure, handle the network dropouts that will happen, and are honest about where RFID pays off versus where a well-implemented barcode is cheaper and more reliable, rather than selling technology the operation does not need.
Cycle counting and inventory control
Continuous cycle-counting programmes (ABC-weighted, location-triggered, exception-driven), that keep accuracy high without shutting the building for a stocktake. We build the counting workflow into the daily rhythm, surface and investigate discrepancies rather than blindly adjusting them, and instrument the drift so the operation can see where accuracy is decaying and why. The goal is stock you can trust enough to commit to a customer, maintained as a routine rather than recovered in an annual panic.
Automation and robotics integration
Integration with the physical automation the building runs on (conveyors and sortation, AS/RS, pick-to-light and put-to-light, and increasingly goods-to-person robotics), engineered with respect for the timing, throughput and failure behaviour of real equipment. We build robust interfaces that keep the software and the machines in agreement about state, degrade sensibly when a device faults, and never assume the hardware will wait politely for a slow transaction, because on the floor a desynchronised conveyor or a confused AS/RS is a stopped line, not a log entry.
3PL and multi-client operations
WMS built for third-party logistics: clean inventory and activity segregation per client, per-client rules and branding, and accurate activity-based billing for storage, handling and value-added services. We design the multi-client model so a new client can be onboarded without reshaping the building, and so the 3PL can prove exactly what it did for whom, because in third-party logistics the billing accuracy and the segregation are not back-office details, they are the commercial model the business runs on.
Where we help
Re-slotting a building that has quietly de-optimised
An operation whose fast movers have drifted to awkward locations and whose pickers walk far too much wants to re-slot without stopping. The real work is trustworthy velocity and affinity data, a slotting model that respects ergonomics and congestion as well as distance, and the ability to move stock into new locations in controlled waves while the building keeps shipping. Done well, pickers walk less on every round from then on; done as a spreadsheet exercise divorced from the live system, the plan is stale before it is executed.
Introducing wave picking to hit despatch cut-offs
A warehouse missing carrier cut-offs because work hits the floor unevenly moves to wave planning. We build wave release that balances labour across zones, feeds packing at a steady rate rather than in lumps, and sequences work to clear each carrier’s cut-off in order. The measurable win is more orders out of the door on time with the same headcount, but only if the waves reflect the real constraints of the building and the carriers, not an idealised flow that ignores where the bottleneck actually is.
Wiring a WMS into an existing conveyor and sortation line
A building with installed conveyor and sortation needs the WMS to drive and track cartons through it reliably. This is hardware integration first and software second: agreeing state with the controls, handling induction and divert timing, coping cleanly when a carton jams or a divert faults, and never losing track of what is where on the line. Get the integration robust and the automation earns its capital cost; get it fragile and every mechanical hiccup becomes a manual recovery that eats the throughput the line was bought to deliver.
Standing up a 3PL client with its own rules and billing
A third-party operator onboarding a new client needs that client’s inventory segregated, its picking and packing rules honoured, its branding on the despatch paperwork, and every chargeable activity captured for accurate billing. We build so the client slots into the multi-client model without bespoke rework of the whole WMS, and so the 3PL can show precisely what storage and handling it performed. That accuracy is what protects the 3PL’s margin and its relationship with the client at the same time.
How we build for warehouse management
We start on the floor, not in the backlog. Before designing anything we want to walk the building through a full cycle (goods-in, put-away, a real pick round, packing, despatch, returns), watch where scans fail and where paper workarounds have crept back, and understand the order profile and the peak. Warehouse software that is designed from a process diagram rather than from the physical operation is the software that gets quietly worked around, so we build from how the operation genuinely runs on its busiest day.
We treat hardware integration as the core risk and resource it accordingly. Scanners, conveyors, AS/RS, pick-to-light and robotics each have their own timing and failure behaviour, and none of them forgives a naive integration or a slow transaction. We plan for the awkward interfaces, the dropped connections and the mechanical faults from day one, and we build the software to keep agreement with the machines and degrade sensibly when a device faults, rather than discovering on go-live that the front end is finished but the floor will not run.
We hold inventory accuracy and throughput as the twin objectives and design the trade-off deliberately. Every movement is scanned and transactionally recorded so stock cannot silently drift; cycle counting runs continuously to catch and correct the drift that remains; picking strategy and slotting are chosen and tuned to the real order profile to keep travel short and throughput high. We instrument both numbers so the operation can see accuracy decaying or throughput sagging and act, rather than finding out during a peak that the design only ever worked on an average Tuesday.
Because we operate what we build, the people who design a wave-release rule or a conveyor interface are the ones who get called at 6am when the line stalls or the counts drift. That concentrates the mind on the failure modes that actually stop a building. A desynchronised sorter, a handheld that dies in the chiller, a peak that outruns the picking strategy, and keeps us honest about trade-offs up front rather than discovering them in production during your busiest week.
Regulation, standards and safety
Warehousing is a physically hazardous environment, and the software runs inside a health-and-safety regime rather than beside it. Under the Health and Safety at Work etc. Act and its regulations, operators of forklifts, mechanised storage and automation carry real duties, and workplace-transport and machinery risks (people working near moving equipment, AS/RS, conveyors and robotics), are among the most serious in the sector. Where our software directs people and machines through the same space, we build with those hazards in mind: sensible interlocks with the automation’s own safety systems, clear task instructions, and awareness that a directed movement must never fight the equipment’s guarding and stop mechanisms.
Traceability obligations depend on what the building stores. Warehouses handling food, pharmaceuticals, alcohol, hazardous goods or age-restricted products carry lot, batch and expiry tracking, recall capability, and sometimes bonded or duty-suspended stock control that reaches into how inventory must be recorded and segregated. We design the WMS to capture batch, lot, expiry and serial data where the goods demand it, and to support the FEFO, quarantine and recall workflows that the relevant regime requires, because for these goods the traceability is a legal and safety obligation, not an optional attribute.
The automation itself sits under machinery safety expectations. AS/RS, conveyors, sortation and robotics are supplied and installed to recognised safety standards with their own guarding, sensors and emergency stops, and the WMS is a system that commands them, not the system that keeps people safe from them. We are deliberate about that boundary: our software must cooperate with the equipment’s safety layer, never override or assume it, and fail into a safe, stopped state rather than pushing work at a machine whose protective systems have intervened.
We build systems that respect these obligations, but we are engineers, not your health-and-safety, customs or regulatory advisers. Duties under health-and-safety law, machinery safety, and any bonded, food or pharmaceutical regime carry real legal weight, and sign-off rests with your own safety, compliance and operations functions and your equipment suppliers. Our job is to build a WMS that captures the traceability those regimes require and cooperates safely with the automation on the floor, and to work alongside the people accountable for them.
Integration
The physical hardware is the integration that defines warehouse software. Rugged handhelds, wearables and vehicle-mount terminals, barcode and RFID capture, conveyors and sortation controls, AS/RS, pick-to-light and put-to-light, weighing and dimensioning, and goods-to-person robotics each have their own interface, timing and failure behaviour. We build robust, well-tested integrations that keep the software and the equipment in agreement about state and degrade sensibly when a device faults, because unlike a business-system API, a conveyor will not wait for a slow write, and a desynchronised machine is a stopped line rather than a retried request.
Upstream, the WMS has to sit cleanly under the systems that own orders and stock at a business level. ERP, order management, and e-commerce or wholesale order sources. Inventory, allocations, receipts and despatch confirmations flow between them constantly, and the WMS is usually the real-time system of record for what is physically in the building while the ERP owns the commercial picture. We engineer that boundary carefully, because a WMS and an ERP that disagree about stock is exactly the drift that ships orders short and erodes trust in both systems.
Downstream, despatch depends on carrier and parcel integration (label generation, manifesting, tracking and the specific rules of each carrier), plus any yard, dock or transport-management systems that schedule the vehicles at the doors. Cut-offs are real and unforgiving, so we build the carrier side to be fast and resilient, because a WMS that picks perfectly but stalls at labelling or manifesting still misses the van, and the whole point of the building is getting goods out of the door on time.
For third-party logistics, integration multiplies: each client may require its own connections to its own systems, its own data formats, and its own reporting. We design the multi-client integration layer so a new client’s connections can be added without reshaping the core, and so activity is captured accurately enough to bill. The recurring engineering problem across all of it is the same as anywhere in logistics (keeping many systems and machines in agreement about state under load), but in the warehouse the machines are physical and the disagreement stops a line, so we treat that reconciliation as core work, not an afterthought.
Security and resilience
The most acute risk in a warehouse is not data theft but downtime, because a WMS is an operational-technology-adjacent system whose failure stops the building rather than merely inconveniencing a user. When the WMS is down, pickers stop, conveyors idle, orders miss cut-offs and the whole operation reverts to paper if it can, and to chaos if it cannot. So we engineer for resilience first: sensible failover, graceful degradation to a mode that keeps the floor moving, and recovery that restores an accurate picture of stock rather than a corrupted one, because in the warehouse, availability is the security property that matters most.
The convergence of the operational floor and the business network is a genuine attack surface. A WMS bridges rugged devices, machine controls and automation with corporate IT and the internet-facing order systems, and that bridge is exactly where operational-technology security incidents happen. We are deliberate about network segmentation between the floor and the office, about not exposing machine controls where they do not belong, and about hardening the devices and interfaces on the operational side, rather than treating the warehouse floor as a trusted zone simply because it is behind a physical door.
For third-party logistics the data itself carries real confidentiality obligations. A 3PL holds several clients’ inventory, order and sometimes commercially sensitive data under one roof, and those clients are frequently competitors. Segregation is a security requirement as well as an operational one: we scope access so one client’s activity, stock and reporting are never visible to another, because a leak across that boundary is both a breach and a lost contract, and the multi-client model has to enforce it structurally rather than by convention.
Because we operate what we build, resilience and security here are not a report handed over at go-live. We instrument the system for the failures that actually stop a building: a device that stalls, a controls integration that desynchronises, a stock picture that starts to drift, keep the audit trail an investigation or a client dispute would need, and rehearse the degraded and recovery modes rather than hoping they work. Treating the ability to keep the floor moving, and to reconstruct exactly what happened, as part of the deliverable is what separates a WMS you can run a peak on from one you merely demoed.
What changes
Inventory accuracy you can commit orders against
Because every movement is scanned and transactionally recorded and cycle counting runs continuously, stock stays accurate enough to allocate and promise without nasty surprises at the shelf, so orders ship complete, availability is trustworthy, and the operation stops absorbing the cost of counts that drifted out of true.
Throughput that holds through the peak
By choosing and tuning the picking strategy and slotting to the real order profile and load-testing for the worst week of the year rather than an average day, the building ships more lines per hour with the same headcount and keeps doing so when volume spikes, instead of reverting to paper the first time demand runs hot.
Automation that stays in step with the software
Because we engineer the hardware integration with respect for real timing and failure behaviour, conveyors, AS/RS and light systems stay in agreement with the WMS and degrade sensibly when a device faults, so the automation delivers the throughput it was bought for instead of turning every mechanical hiccup into a manual recovery.
What we build for warehouse management
From a first platform to modernising what you already run. The disciplines this sector draws on most.
How we deliver
- 01
Discover
We map the system, the constraints and the business it serves, including the parts nobody documented.
Architecture brief
- 02
Architect
Decisions get made, written down and defended before a line of production code exists.
Decision records
- 03
Build
Short cycles against working software. You see progress in the product, not in a status deck.
Shipping increments
- 04
Operate
Monitoring, incident response and iteration. The system is alive, so the engagement is too.
Runbooks & SLOs
Building something for warehouse management?
Tell us the problem and the constraints you are working under. A senior engineer will give you a straight view on what it would take, and say so plainly if we are not the right team for it.
Technologies we work in
Chosen per problem, not per fashion. A selection of the stack we most often reach for.
Why teams in warehouse management choose us
We build from the floor, not from a process diagram
The reason WMS projects get worked around is that they are designed from an idealised process the operation does not follow. We walk the aisles, watch a real pick round and design for how the building genuinely runs on its busiest day, because a WMS the floor routes around, however tidy its model, has delivered nothing.
We treat hardware integration as the hard part it is
Scanners, conveyors, AS/RS, pick-to-light and robotics are where warehouse projects are won or lost, and none forgives a naive integration. We resource that from day one and build software that keeps agreement with the machines and degrades safely, which is what separates a WMS wired properly into the floor from one that ships half-connected.
We hold accuracy and throughput together honestly
These two goals pull against each other, and pretending otherwise is how a design fails at peak. We engineer the trade-off deliberately, instrument both numbers, and will tell you plainly where chasing one is costing you the other, rather than selling a system that only ever worked on an average Tuesday.
We operate what we build
The people who design a wave-release rule or a conveyor interface are the ones paged when the line stalls or the counts drift at 6am. That keeps us focused on the failure modes that actually stop a building and honest about trade-offs up front, not discovering them in production during your busiest week.
Related sectors
Part of Logistics & Supply Chain. Adjacent sectors we also know.
Common questions
How do you keep inventory accurate in a busy, constantly moving warehouse?
By making sure no physical movement goes unrecorded and by finding drift continuously rather than annually. Every receipt, put-away, move, pick and return is scanned and transactionally recorded so the system and the shelf cannot silently disagree, and we build continuous cycle counting (ABC-weighted, location-triggered and exception-driven), into the daily rhythm so discrepancies are caught and investigated rather than left to accumulate. We also instrument the drift so the operation can see where accuracy is decaying and why. The aim is stock you can trust enough to commit to a customer, maintained as a routine, not recovered in a disruptive stocktake.
Can you integrate our WMS with conveyors, AS/RS, pick-to-light or robotics?
Yes, and we treat that as the core risk of the project rather than a late add-on. Physical automation has its own timing, throughput and failure behaviour, and a conveyor or AS/RS will not wait for a slow database write, so we build robust interfaces that keep the software and the machines in agreement about state and degrade sensibly when a device faults. We are also deliberate about the safety boundary: our software commands the equipment and cooperates with its own guarding and emergency stops, it never overrides or assumes them. Underestimating this integration is the classic way a WMS ships late and half-connected to the floor, so we resource it from day one.
Which picking strategy should we use, batch, wave, zone?
It depends on your order profile, building layout and volume, not on fashion, and a building often needs more than one running at once. Small single-line web orders suit batch or cluster picking; large multi-line wholesale orders suit discrete or zone picking with wave release to hit carrier cut-offs. We treat the choice as an operations and engineering decision driven by real data, and we build so the strategy can be tuned and combined as your order mix changes, because the picking method is the single largest lever on how much the building can ship, and the wrong one taxes travel time on every order all day.
Will the system cope with our peak, not just normal volume?
That is exactly what we design and test for, because peak is the only week that really matters and it is where average-case designs collapse. We load-test against the worst week of the year (the promotion, the seasonal surge, the Black Friday multiple), and stress the picking strategy, slotting, hardware and software together, because those are what get tested at once when the operation runs hot. We also build sensible degraded modes so a hiccup slows the floor rather than stopping it. A WMS that only works on an average Tuesday is a promise you cannot keep in December, and we would rather find its limits in a load test than in production.
Do you build WMS for third-party logistics with multiple clients?
Yes, and the multi-client layer is a whole dimension of complexity a single-owner warehouse never faces, so we design for it deliberately. Each client needs its inventory and activity cleanly segregated, its own picking, packing and branding rules honoured, and every chargeable activity (storage, handling, value-added services), captured for accurate billing. We build so a new client can be onboarded without reshaping the core WMS, and so the 3PL can prove exactly what it did for whom. The segregation is a security requirement too, because your clients are often competitors, so we enforce it structurally rather than by convention: the billing accuracy protects your margin and the segregation protects your contracts.
Building for warehouse management?
Tell us what the system has to do and what it cannot get wrong. A senior engineer reads it, and if warehouse management is not a domain we know well enough to be useful in, we will say so rather than learn it on your budget.
- 01A senior engineer reads it. Not a form queue, and not an account manager.
- 02We reply either with questions or with a straight answer that we are not the right fit.
- 03If it looks like a fit, a technical call with the person who would actually run the delivery.
- 04Then scope, effort and risk in writing, before anyone signs anything.