Maddy Alcala, Author at OrderMesh

The Four Types of POD Software and What Each One Actually Does

Posted on May 6, 2026May 6, 2026 by Maddy Alcala

Many print-on-demand technology buying decisions go wrong before any vendor is ever evaluated because the buyer doesn’t have a clear picture of which software category solves which problem. As a result, they either buy the wrong tool for the job or they ask one tool to do the job of three and wonder why nothing works the way it should.

This is a quick reference guide to the four types of software you’re likely to run into if you’re evaluating tech for your POD operation. I’ll cover what each one does, what it doesn’t (or shouldn’t do), how to tell these systems apart, and example platforms in each category.

Layer 1: The Shop Floor / Workflow Management System

What it is: The software that runs production inside a facility.

A shop floor or workflow management system (sometimes called a WMS, MIS, or production management system depending on the segment) is concerned with one thing: getting physical work produced correctly and on time. It usually manages job scheduling, machine queuing, print file preparation (sometimes), operator task assignment, quality checkpoints, and production reporting. It speaks the language of the production room, including things like imposition, ganging, substrate types, color profiles, decoration methods, and press schedules.

What it knows: What machines you have, what they can produce, what’s queued up, and what’s currently running.

What it might not know: Where the order came from, what channel it was placed on, how it should be priced, or what happens after it ships.

The key distinction: A shop floor system operates inside the four walls of a production facility. Its job begins when a production job arrives and ends when that job ships. It is not responsible for deciding whether a job should come to this facility in the first place, and it usually has no native mechanism for receiving orders from external customers or routing to partner facilities.

How to recognize it in a demo: The screens show job queues, machine capacity, color calibration workflows, and operator assignments. The conversation is about throughput, turnaround, and visibility at the machine level.

Examples: Printavo (screen printing and decorated apparel), EFI Pace (wide-format and commercial print production), Print Factory (large-format and digital print workflow and color management), Shopworks (decorated apparel and promotional products shop management), Gelato Connect (production job intake and management for Gelato’s partner print facilities), Fulfill Engine (POD and decorated product shop floor / job management).

Layer 2: The Enterprise Resource Planning System (ERP)

What it is: The system of record for your business finances and operations.

An ERP is the financial and operational backbone of the business. It manages general ledger accounting, accounts payable and receivable, inventory valuation, purchasing, fixed assets, and financial reporting. It is the source of truth for what your company owns, what it owes, what it has spent, and what it has earned.

In a production environment specifically, the ERP manages pricing, the bill of materials, and tracks raw material inventory. It is the system that knows how much blank stock is on hand in a given warehouse, what a job cost to produce, and how to record that cost in the general ledger.

What it knows: Your financials, your inventory at facility level, your supplier purchase orders, your cost of goods, your payroll.

What it doesn’t know: Which of your five production facilities should receive an inbound order from a new eCommerce customer, how to normalize product data across suppliers with different catalog formats, or how to onboard a new customer through a self-service API. When ERPs try to do order management, the result is typically slow, manual, and brittle under volume.

How to recognize it in a demo: The screens show charts of accounts, purchase orders, inventory transactions, financial statements, and maybe HR records. The conversation is about month-end close, audit trails, and compliance.

Examples: SAP (large enterprise standard), Oracle NetSuite, Microsoft Dynamics 365, Odoo (modular open-source ERP common in mid-market operations that need financial and operational management without SAP-scale implementation overhead).

Layer 3: The Order Management System (OMS)

What it is: The coordination engine between where orders are placed and where they get fulfilled.

This is the layer that causes the most confusion, because it sits between the other systems and its job is invisible when it’s working well. An OMS receives orders from one or more commerce channels — eCommerce storefronts, marketplaces, company store platforms, B2B portals, API-connected platforms — and makes the decisions about how and where those orders get fulfilled. It applies routing logic, normalizes product data across suppliers or locations that all use different formats, manages split shipments, handles exceptions when something goes wrong, and gives everyone in the operation end-to-end visibility from order placed to order shipped.

The OMS is the system that answers questions like: this order has three items — one we produce in-house, one our partner in Dallas can fulfill faster, and one that needs to ship from our wholesale supplier. How do we treat that as one clean customer experience while executing it across three different production sources? That problem is called mixed-channel fulfillment, and it’s one of the hardest things to do well in print and POD. The shop floor system can’t solve it because it only sees its own queue. The ERP can’t solve it easily because it wasn’t built for real-time external routing. The store platform can’t solve it because it has no production logic. The OMS is the only layer whose job this actually is.

A well-built OMS can also handle customer or sales channel onboarding for print suppliers. Modern digitally native brands expect a self-service API portal, interactive developer documentation, sandbox environments, and the ability to start sending orders without a manual integration project on either side. If your “integration” process involves back-and-forth emails and a months-long implementation, you don’t have a simple front door for your business that new customers can walk through without encountering friction. Sometimes the WMS provides this integration tooling too but OMS systems are typically much more flexible in accommodating complex customers and/or those who need multi-channel fulfillment.

What it knows: Every order from every channel, which vendor or facility is fulfilling each item, where each order is in the fulfillment lifecycle, and when something goes wrong.

What it doesn’t know: How to run your machines, what your general ledger looks like, or how to display your product catalog to a customer.

The key distinction: The OMS sits above the shop floor and next to the ERP. It doesn’t replace either one. It is the decision layer that determines where work goes before the shop floor receives it and before the ERP records it. If you remove it, someone is probably making those routing and exception decisions manually or this logic is hard-coded into your eCommerce backend or WMS.

How to recognize it in a demo: The screens show order dashboards across multiple sources, routing rule configuration, vendor network management, exception queues, and API documentation. The conversation is about integration speed, routing logic, and what happens when a vendor fails a job. If someone is walking you through how to configure a routing rule, you’re in this layer.

Examples (traditional retail/enterprise): Manhattan Associates OMS, IBM Sterling Order Management, Salesforce Order Management. Examples (print and POD-specific): OrderMesh.

Layer 4: The Store, eCommerce Platform, and/or Front End

What it is: The tech the customer sees and interacts with.

This is where transactions happen and this tech includes the storefronts, the product configurators, the checkout experience, the customer account portal, the design tool, and the marketplace listing. This layer is responsible for the buying experience, the presentation of your product catalog, the pricing the customer sees, and the payment transaction. It is the revenue surface of your business.

A well-built front end is optimized for one thing: converting a visitor into a buyer and making that experience fast, clear, and trustworthy. It should not be carrying production routing logic, vendor selection rules, or fulfillment orchestration. When store platforms are asked to do those things, they become slow and brittle, and they break when order complexity increases or a new production source is added.

Design and editor tools like Fast Editor also live at this layer or immediately adjacent to it. They sit between the customer experience and the order handoff to the orchestration layer. Getting the hand-off from design tool to production file clean and automated, without a manual step in the middle, is one of the most operationally impactful integrations a print business can make.

What it knows: What your customer wants to buy, what they’re willing to pay, and what they experienced during the transaction. The store platform’s job ends at the order. Everything that happens after the “place order” button is pressed belongs to the OMS and the production layer.

How to recognize it in a demo: The screens show storefronts, product pages, checkout flows, and customer account dashboards. The conversation is about conversion rate, page speed, and customer experience. If the pitch involves themes, templates, or abandoned cart recovery, you’re in this layer.

Examples: Shopify (dominant in DTC eCommerce), WooCommerce (WordPress-native, open source), Magento / Adobe Commerce (complex B2B and enterprise commerce), BigCommerce, Salesforce Commerce Cloud. At the marketplace and social commerce level: Amazon, Etsy, TikTok Shop. In company stores and promo: Brikl, Order My Gear / Brightstores, Chipply.

Every System Is the Source of Truth for Something.

The cleanest way to draw boundaries between these four layers is to ask a simple question about each one: what is this system the authoritative record for? When there’s a dispute, a question, or an audit, where does the definitive answer live?

The ERP is the system of record for your business finances. What did this job cost to produce? What does this vendor invoice say? What is the inventory valuation at this facility? What did the company earn last quarter? The ERP owns those answers.

The shop floor system is the system of record for what happened inside production. Was this job produced? When did it complete? Which operator ran it? Did it pass quality control? What machine was it run on? The shop floor system owns that history. No other layer has visibility into the production execution record the way the shop floor tool does.

The store platform is the system of record for the customer transaction. What did the customer order? What price did they pay? What did they see in the checkout? What is their account history? The storefront owns the commercial relationship with the buyer and the record of every interaction within it.

The OMS is the system of record for the order across its entire lifecycle, from the moment it enters the network to the moment it’s fulfilled. Which vendor was it routed to and why? When did it change status? What happened when it failed and how was it resolved? How many orders moved through the network this week, from which channels, to which production sources? No other system in the stack has that end-to-end view, because no other system sits in the middle of all the others.

This is also where most stacks break down. The shop floor system knows what was produced but not where the order came from. The ERP knows what it cost but not which channel originated it. The store platform knows what was ordered but not whether it was fulfilled correctly. Without an OMS connecting and tracking across all of them, the end-to-end order record lives in nobody’s system, which means it lives in a spreadsheet, an inbox, or someone’s memory.

Why the Most Competitive Businesses in Print-On-Demand Are Building Networks, Not Facilities

Posted on April 27, 2026April 27, 2026 by Maddy Alcala

There is a seductive logic to owning your own production. You control quality and capacity. You control the customer relationship from the moment an order arrives to the moment it lands on a doorstep. For most of the history of the print and decorated products industry, that logic was sufficient but it is becoming less so.

Not because ownership is the wrong instinct, but because the economics of getting a product from a facility to a customer have shifted in ways that a single production location, no matter how well-run, was not designed to absorb. Shipping costs are rising and consumer expectations around delivery speed have tightened considerably. Product breadth demands are expanding and geographic reach has become a competitive variable rather than a fixed constraint. The businesses responding most effectively to these shifts are not the ones that built a better facility. They are the ones that built a network.

A Tax on Distance

For most ecommerce businesses, shipping runs between 10 and 15 percent of total order value or more. In categories like decorated apparel and promotional products, where margins are already under pressure and average order values are not enormous, that is a meaningful slice of every transaction. And it has been growing. Shipping costs in the United States have risen more than 40 percent over the past five years, with UPS and FedEx both raising rates by roughly 5.9 percent in 2024. The postal service followed in 2025.

What is often discussed less is that shipping cost is not purely a function of weight or carrier selection. It is heavily a function of distance, specifically the number of shipping zones a package crosses between the facility where it was made and the address where it is going. A decorated t-shirt shipping from a single facility on the West Coast of the US to a customer in Boston may cross four, five, or six zones. Move the production closer to the customer and the same package might cross one or two. That zone compression, which sounds like a logistics detail, can reduce per-shipment cost by 30 to 50 percent on a given order.

That is not a theoretical efficiency. It is money that currently leaves the business on every package.

The consumer side of the equation adds another layer of pressure. Fifty-eight percent of global shoppers cite high delivery costs as their primary source of frustration when shopping online. Nearly half of all online shopping carts are abandoned because of unexpected fees added at checkout. Sixty-three percent of consumers say they will take their future business elsewhere if a first delivery takes longer than two days. These figures come from ecommerce research, but they describe the customers of your customers. That pressure does not stop at the storefront. It travels up the supply chain and eventually arrives at the production decision.

The Lesson from Logistics at Scale

The most rigorous real-world test of the proximity principle did not happen in the print industry. It happened at Amazon.

By 2021, Amazon’s fulfillment network had grown so large and so quickly that its own scale had become an operational liability. Orders were being shipped from wherever capacity existed rather than wherever it made geographic sense. Costs were rising and delivery times were not improving despite continued infrastructure investment. The company committed to a significant restructuring built around a single organizing idea: divide the country into eight largely self-sufficient regions, stock each region with enough inventory and capacity to serve customers within it, and route the overwhelming majority of orders to the production or fulfillment node closest to the destination.

The outcome was that 76 percent of Amazon’s order volume shifted to being fulfilled from within the customer’s own region. Delivery times fell. Transportation costs fell. Amazon has since continued refining the model, working toward even smaller, more localized regions, because the data keeps confirming the same thing: proximity to the customer is not a convenience. It is an economic advantage that compounds.

Amazon has applied this logic to print directly, opening a print-on-demand facility in Florida specifically to produce books locally and support faster, cheaper fulfillment for customers in the region.

The print industry did not invent this problem, and it does not need to invent the solution. The solution is already well-documented. What it requires is the willingness to organize production around a network model rather than a single-source model, and the infrastructure to route orders across that network intelligently.

If You Own the Equipment

For businesses that own production capacity, the case for a network mindset tends to arrive in one of three forms, usually in this order: a peak season that overwhelms the facility, a customer that asks for a product category outside the core, or a new client in a geography that the current location cannot serve economically.

Each of these is a version of the same underlying problem. A single facility is optimized for a specific set of conditions: a particular product mix, a particular production volume, a particular geographic footprint. Outside of those conditions, it has limited flexibility. It cannot add capacity without capital. It cannot add capability without equipment and expertise. It cannot add geographic reach without a second location.

A network extends all three without requiring any of it.

Overflow capacity is the most immediate application. When a facility is running at capacity and a new program arrives, the business faces a binary choice: accommodate it or decline it. A production business with established network relationships has a third option. It routes the overflow to a trusted partner, retains the customer relationship, collects the margin, and does not turn away revenue. This is not an exotic arrangement. It is how the most sophisticated operators in the market have managed demand variability for years.

Product expansion is the second application. The market is converging. Commercial print, apparel decoration, promotional products, hard goods, and branded packaging are increasingly being purchased by the same buyers through the same channels. A brand that works with a production partner for decorated apparel increasingly wants that same partner to handle the hard goods component of a campaign or the kitting. A production business that can only say yes to a portion of that request is a production business that is gradually being designed out of larger programs. Filling the gap through a network partner is often faster, less capital-intensive, and lower-risk than building the capability internally, and it lets a business test category demand before committing to the investment.

Geographic reach is the third. A single facility serves the geography around it efficiently and the rest of the country at an increasing cost disadvantage. As customers grow and their own footprints expand, the production partner that can meet them across regions becomes structurally more valuable than the one that cannot. A network makes that coverage available without opening a second facility.

If You Don't Own the Equipment

For businesses that source production rather than own it, the argument is even more direct.

A single production partner is a single point of failure. Equipment goes down. Capacity fills. Quality inconsistencies emerge. Pricing changes. When any of these things happen and there is no routing alternative, the exposure is total. The customer relationship absorbs the disruption regardless of where the fault originated.

But the risk argument, while real, is less compelling than the opportunity argument. The more important reason to build a distributed production footprint is not what it protects against. It is what it makes possible.

Geographic coverage means that orders are fulfilled closer to the customers receiving them. The shipping cost savings either improve margin or get passed along as a pricing and speed advantage, which in a market where 88 percent of consumers say free shipping matters more to them than fast delivery, is a meaningful lever. Capability breadth means a more complete program offering without being constrained by what a single vendor can produce. Capacity resilience means that demand growth, seasonal spikes, and successful program launches do not immediately become fulfillment problems.

The platforms and programs that have built this kind of distributed footprint deliberately operate with a fundamentally different posture than those still organized around a single production relationship. They are not immune to disruption. They are structured to absorb it, route around it, and keep the customer experience intact regardless.

The Infrastructure Behind the Network

None of this is self-executing. A network of production partners without intelligent routing is not a network. It is a vendor list with a manual decision-making process sitting in the middle of it.

What Amazon’s regionalization story is really about, beneath the fulfillment center geography and the supply chain research, is a software and data problem. The physical facilities existed. What changed was the logic governing which facility fulfilled which order, optimized in real time across proximity, available capacity, product capability, and cost. The network became more valuable not because Amazon added more buildings, but because it got better at routing across the ones it had.

The same dynamic applies in print. A production network is only as strong as its ability to move the right order to the right node at the right moment. That requires catalog normalization across vendors, routing logic that accounts for capability and geography, exception handling when a primary route is unavailable, and visibility across the entire order flow. Without that infrastructure, every new partner added to the network adds operational complexity rather than operational leverage.

This is the gap that most operators are still working in. And it is the gap that separates businesses that can genuinely scale a distributed production model from those that are simply managing a more complicated version of the same manual process.

The single-source model served the industry well for a long time. It offered simplicity, control, and predictability. What it cannot offer, in the current environment, is the geographic flexibility, the capacity resilience, and the cost efficiency that a distributed network provides when it is built and operated correctly.

The shift is not about abandoning what has worked. It is about recognizing what the next phase of this market requires, and building the infrastructure to compete in it.

Two Industries Sitting on Exactly What the Other Needs

Posted on April 16, 2026April 16, 2026 by Maddy Alcala

I attended Kornit Konnections this week and spent most of my time listening to retailers describe their own problems, mostly disconnected systems and planning calendars that had quietly become constraints rather than tools. But the elephant in the room was the problem that retail has been trying to solve for 20+ years: inventory.

There is a particular kind of organizational pain that comes from knowing exactly what is wrong and being structurally unable to fix it. Retail has been living with that pain around inventory for a generation.

On the balance sheet, finished goods inventory looks like an asset. To a lender, it is collateral. Banks typically advance between 50 and 80 percent of appraised inventory value against it. Public markets treat inventory turns as a signal of operational health. Entire finance functions have been built to optimize these numbers, and for a long time the model held together well enough. The cracks in that model are widening.

In 2023, the fashion industry produced somewhere between 2.5 and 5 billion unsold garments, representing an estimated $70 to $140 billion in retail value sitting in warehouses, on markdown racks, or written off entirely. Nike reported in 2024 that markdowns affected 44 percent of its assortment, more than double the figure from two years prior. The cost of holding unsold inventory typically runs 20 to 30 percent of product value per year so a garment worth $100 costs $25 to carry for twelve months. Across millions of units, the math becomes unforgiving.

The root cause of this is structural. Most retail planning still operates on a 12 to 18 month calendar, with buyers committing to finished goods nearly a year before a consumer ever sees them. The strategy can work brilliantly for brands that correctly predict what consumers will want six or nine months out. But for every brand riding high on the right bet, there is another working through an inventory overhang it cannot move. This planning and purchasing calendar is not just a process. It runs through organizational structure, vendor contracts, financing covenants, and incentive systems built around certainty that the market rarely provides, especially now.

Retail has been talking about fixing this problem for two decades and largely has not because of the complex change management problem embedded in how retail companies are built, capitalized, and led.

I listened to a panelist at Kornit Konnections talk about a solution. He spoke about how the longest lead time in any apparel value chain is the raw material component. The more finished a product is when you take a position on it, the worse your flexibility when demand shifts. The brands that win the flexibility game are the ones that take positions on the raw materials underlying the majority of their volume and hold inventory in its most configurable, unfinished state for as long as possible. Imagine a roll of fabric before it is printed, dyed, or decorated. This approach preserves optionality.

While I was listening to this panelist talk, I thought of the dozens of print-on-demand facility tours I’ve done over the years. POD operators have understood this plan instinctively for years.

What POD has gotten right by necessity

Print-on-demand businesses were not built around a planning calendar because they could not afford to be. With no MOQs or bulk buys, why or how could you hold onto warehouses of finished goods, all wagered on demand that has not yet materialized. The entire POD model was constructed around a single structural insight: produce only what is ordered, when it is ordered, and hold raw material in its most configurable state until the last responsible moment.

Companies like Kornit Digital have built their entire operating thesis on this principle, making the case that businesses should not hold inventory they have not yet sold. The economics are not complicated. The capital efficiency is real. The inventory risk is structurally neutralized rather than managed after the fact.

This is what retail needs to borrow. Not just the philosophy, but the operating model behind it. The two-week product drop, executed through a small nimble team or through vendors taking product to market directly on a brand’s behalf, is not a fantasy. It is already happening with brands who have punched through the change management challenge. The brands not doing it are mostly waiting for their planning process to approve something the market already validated.

What POD has not figured out yet

As I was listening to these same retailers talk, I also ruminated on what I think is a harder truth that tends to get less airtime at POD-centered industry events.

The flexibility that makes print-on-demand structurally superior is also the thing that keeps most POD businesses from becoming “real” brands. When you never fully commit to a product, you never fully commit to a point of view, which is what brands are built on. The blank t-shirt that can become anything is, in a meaningful sense, nothing in particular until a decision is made about what it should be. I think back to a conversation I had with the COO of one of the original POD-native marketplaces — she told me her organization was moving away from POD as a supply chain strategy because the products weren’t unique enough and she couldn’t hold onto her customers’ loyalty. Her brand had lost its point of view by relying 100% on a POD model.

Retail, for all its dysfunction, has produced enormously wealthy companies and operators because the model generates real brand equity, real consumer loyalty, and real pricing power. That value compounds over decades. POD has largely produced high-volume, low-margin fulfillment infrastructure that struggles to hold pricing because differentiation is thin and switching costs are low. The moment a POD operator or brand starts spending like a retailer, without the brand equity to support it, the economics unravel. The capital efficiency that makes the model attractive disappears the instant traditional retail cost structures get layered on top of unit economics that were never designed to carry them.

The financial disparity between the two industries tells this story precisely. The global retail technology solutions market reached $234.5 billion in 2023. In a single quarter of that same year, retail tech financing deals alone totaled $4.7 billion. More than 18,000 venture capital investors are active in the space. Against that backdrop, the entire print-on-demand software market is estimated at $4.5 billion in total market size in 2025. Not invested capital. Market size. The POD largest fundraising round into pure software ($260mm into Gelato) is the major VC financing deal of this decade, and that is no discredit to Printify who raised material capital around the same time.

This comparison is not a criticism of POD software but rather a precise measurement of how differently capital has flowed into these two industries, and how much of the capability gap between them traces directly back to that difference.

That capital built something specific in retail and did not just fund talented people. That money has built the data infrastructure, the demand forecasting systems, and the organizational muscle required to move from operator-driven decisions to systems-driven flows. The Harvard MBA founders and McKinsey-trained data scientists who entered retail over the past two decades tell another story of this funding, technology, and talent gap. The destination retail is sprinting toward, thanks to the large amount of money that has flowed into that world, is a business where systems handle the routine decisions, humans make the judgment calls, and the gap between sensing demand and responding to it collapses toward zero. POD is, by and large, still at the beginning of that journey.

The shift that changes everything

The transition from operator-driven decisions to systems-driven flows is the defining operational shift of this decade, and it is arriving in both industries simultaneously, though from very different starting points.

Retail built toward this transition over decades of capital investment and institutional development. The infrastructure exists. The discipline exists. What retail is now discovering is that the systems it built to optimize a calendar-planning model are capable of something far more dynamic, if the organizational will is there to let them evolve.

POD is approaching the same transition from the opposite direction. Less infrastructure. Less institutional data. Less financial backing. But a model that is already structurally aligned with on-demand, unit-level economics.

AI and autonomous workflows are an accelerant for both industries, if used correctly. AI can be a great equalizer for the POD market if we leapfrog ahead in how we build software, analyze data, and solve complex data and systems integrations. AI can help us close the distance between the instinct-driven POD operator and the analytically rigorous retail planner. The data sophistication that retail spent decades and billions building is becoming accessible in compressed time and at a fraction of the historical cost. The POD business who makes routing decisions, pricing adjustments, and replenishment calls by feel will be competing against systems that make those same decisions in milliseconds, with full visibility across every variable. That is not a threat to dismiss. It is an invitation to build.

The most important variable is still the people

I think that the POD and retail industries are missing deliberate cross-pollination of talent. The POD industry needs more operators who have run sophisticated retail planning functions and supply chains, who have sat inside organizations where Harvard MBA founders set the strategic direction and McKinsey-trained data science teams built the analytical infrastructure beneath it. People who understand what it means to manage inventory at scale, build a brand that commands pricing power, and run a business with the financial discipline the next stage of growth actually requires. Retail needs people who have built nimble, inventory-light operations from the ground up, who understand configurable supply chains, unit-level economics, and what it actually means to take a product to market in two weeks without a planning committee signing off on it.

Right now, those two talent pools barely intersect. That is one of the most consequential gaps in either industry and one of the least discussed, in my view. The conversations happening inside POD companies and inside retail organizations are almost entirely separate. The insights being generated on one side are not reaching the other.

That is the conversation worth having and Kornit Konnections made huge strides this week in starting it. I applaud Kornit for a fantastic show that recognized how much retail and print-on-demand have to offer each other. These industries have more to offer each other than either has been willing to admit, and the window to act on it, before systems make the capability gap irreversible, is open right now.

Don’t Buy Software, Make an Infrastructure Decision

Posted on April 9, 2026April 9, 2026 by Maddy Alcala

Why the tech you use right now will determine your competitive position for the next decade: what to look for in a platform built for what comes next.

There is a question that every CEO in the print and promotional products supply chain is eventually going to face. Most of them are already facing it, whether or not they have named it as such.

The question is not which software platform has the best feature set today. The question is which technology architecture will still be serving your business effectively in three years, in an environment that is changing faster than any roadmap can predict.

The Environment Your Next Software Decision Will Actually Operate In

The scale of investment flowing into AI and software infrastructure right now is unlike anything the technology industry has experienced before. Microsoft, Google, Amazon, and Meta are collectively deploying hundreds of billions of dollars annually into AI infrastructure, foundation models, and developer tooling. A generation of well-funded AI labs is compressing years of software development capability into months. The pace of change is not a temporary spike and by every credible measure, it is accelerating.

For a CEO in the print or promotional products supply chain, this matters in a specific and practical way: the software platform you select in the next twelve months will be operating in this environment for the next five to seven years. The question is not whether that platform handles your current workflows. It is whether its underlying architecture can absorb what the market demands next without requiring you to rebuild from scratch when the next capability shift arrives.

That shift is not hypothetical. It is already visible. AI agents that browse, select, and fulfill on behalf of buyers are moving from research projects to production deployments.

Hyper-personalized content, generated at the individual recipient level, is becoming the input that feeds print production at scale. Sales channels are multiplying faster than integration teams can keep pace with. Production networks are becoming more distributed, more global, and more capability-diverse with every quarter.

The technology decisions being made right now are not decisions about features. They are decisions about architecture. And architecture decisions compound — in both directions.

The businesses that built on open, API-first, cloud-native infrastructure during the shift to SaaS a decade ago compounded their advantage with every year that passed. The ones that stayed on legacy systems spent the next decade paying to migrate. The same dynamic is playing out now, faster, with AI as the forcing function.

Anyone Can Write Code Now. That Is Not the Same as Building Infrastructure.

One of the most significant developments in the technology landscape over the last two years is the emergence of AI-assisted coding tools that have dramatically lowered the barrier to writing functional software. A single developer, or in some cases a non-developer, can now produce working code at a pace that would have been impossible three years ago. The industry calls this vibe coding: rapid, AI-assisted software development that produces functional outputs quickly, often without deep architectural planning.

This is genuinely useful for prototypes, internal tools, and simple automations. It is not a substitute for production-grade engineering infrastructure. And this distinction matters enormously for any CEO evaluating platforms to run mission-critical order management, fulfillment routing, and supplier connectivity.

The gap between vibe-coded software and production-grade infrastructure is not visible in a demo. It shows up months or years later, in specific, costly ways that are difficult to reverse.

Security is the most immediate risk. Production systems handling order data, customer records, and supplier integrations are targets. SOC 2 compliance is not a certification that can be acquired after the fact; it is a continuous engineering discipline that requires dedicated security investment, regular audits, penetration testing, and documented controls. Most rapidly-built systems do not have it. The exposure is real and the liability compounds with every enterprise customer you add.

Scalability is the second failure mode. Software that works cleanly in a demo environment and software that processes hundreds of orders per second under sustained production load are different engineering problems. Auto-scaling infrastructure, event-driven architecture, and self-healing systems require deliberate architectural decisions that cannot be retrofitted. They have to be built in from the start or you rebuild when volume exposes the gaps.

The third failure mode is the one most CEOs do not see coming until it is expensive: API fragility. Every supplier, every sales channel, and every business system that connects to your order management platform depends on stable, versioned APIs with documented change management. A platform without disciplined versioning forces every integration partner to absorb the cost of breaking changes. That cost multiplies with every new connection added to the network. And in the print and promotional products supply chain, the network is the business.

The moat is not the ability to build software. Anyone can do that now. The moat is the ability to build software that is secure, scalable, and architected to evolve without constant rebuilding.

The Giants Are Setting the Bar

The technology arms race is not abstract. It is playing out in the specific platforms and capabilities that the largest players in adjacent markets are deploying right now and those deployments are setting the technical expectation floor for every supplier and operator in their orbit.

Shopify has invested heavily in making its platform the default commerce layer for businesses that sell physical products online. Its developer ecosystem, its APIs, and its logistics network are all moving toward deeper integration with on-demand production. Any order management platform that cannot integrate cleanly and reliably with Shopify and with the commerce platforms that follow is already behind.

Amazon continues to raise the bar on what sellers and fulfillment partners are expected to deliver: speed, real-time visibility, automated exception handling, and zero tolerance for manual intervention in high-volume workflows. Those expectations do not stay inside Amazon’s ecosystem. They migrate across every sales channel your customers use.

Canva’s expansion into print is the most instructive example for anyone in this space. Canva built an API layer connected to production networks and made the entire backend invisible to their users. Every print business that wants to work with the next platform like Canva needs to be technically capable of connecting on demand, at scale, with no manual work required on either side.

In promotional products specifically, distributors on modern software are going to route work to suppliers who can receive and process orders programmatically. The ones who cannot will find themselves progressively excluded from the programs that matter most.

The competitive dynamic here is asymmetric. Platforms and brands building modern, API-first infrastructure get more capable with every integration they add. The businesses running on legacy systems fall further behind with every integration they cannot make. The gap compounds. It does not close on its own.

What to Look For in a Platform Built for What Comes Next

The specific features a platform offers today are less important than the architectural decisions underneath them. Here is what to evaluate when selecting technology infrastructure for an environment that will look fundamentally different in 24 months.

API-first with documented versioning. Every capability available through the user interface should be available through the API. Versioning should be explicit, with documented deprecation timelines and advance notice. This is the architectural prerequisite for any future integration — with AI tools, with new channels, with new production partners — to be built reliably and maintained without constant renegotiation.

AI-native integration capability. The Model Context Protocol is becoming the standard interface through which AI agents interact with software systems. A platform with a documented MCP server is already built for AI-native operation. A platform without one will require architectural work to support the AI integrations that are coming and they are coming faster than most roadmaps anticipate.

Event-driven architecture. Systems that push events rather than requiring polling are fundamentally better positioned for AI integration, real-time operational visibility, and automated exception handling. Event-driven architecture also provides resilience during outages: events queue rather than drop, and the system recovers to a consistent state without manual intervention.

Open integration framework. A platform that connects to any ERP, any commerce platform, any editor tool, and any production management system through documented APIs is a platform that can grow with the ecosystem. A platform that requires custom development for every new connection creates technical debt with every integration added.

Security as architecture, not certification. SOC 2 compliance is not a document that can be acquired after a system is built. It is an engineering discipline that must be designed in from the beginning. Ask any vendor you are evaluating to walk you through their security controls, their audit cadence, and their data isolation architecture. If they cannot answer fluently, you are looking at a system that was not built with security as a design constraint.

Ask any software vendor you are evaluating: what does your architecture look like when AI agents are placing orders, when a new sales channel launches overnight, and when your production network doubles in 90 days? The answer will tell you everything about whether that platform was built for today or for what comes next.

Why This Is the Moment to Decide

There is a specific window of competitive opportunity that opens during periods of rapid technology change. The businesses that make the right infrastructure decisions before the market fully absorbs what is happening compound their advantage with every passing month. The ones that wait discover that the gap they were avoiding closed and a larger one opened in its place.

That window is open right now in the print and promotional products supply chain. The structural shift toward on-demand production is accelerating. The technology environment is changing faster than any individual business can track. The competitive consolidation that reshaped the industry in 2024 and 2025 is not finished — the next wave will reward the businesses with the infrastructure to operate across category lines and at the technical sophistication level that modern buyers and channels require.

The businesses making the right technology decisions now are not solving a software problem. They are building a network, including a connected system of production partners, sales channels, and operational workflows that becomes more valuable and more defensible with every integration added. The software is the foundation. The network is the competitive moat.

OrderMesh was built for exactly this environment. The platform is API-first, SOC 2 compliant, event-driven, and MCP-enabled. It was built by a team that has been using AI in its own development cycle for over two years. It is backed by Taylor Corporation, one of the largest commercial print operators in the world, which evaluated the entire market, chose OrderMesh to solve its own digital transformation, and then acquired the company to power its future. That sequence is not a footnote. It is the proof that this platform was built for serious operations at serious scale.

Is your current infrastructure built for what comes next?

We put together 10 questions every business should ask their print order management provider. If your vendor cannot answer them, you are likely carrying technical debt that will become a competitive liability before you expect it. You can find the 10 questions below.

10 Topics to Cover With Your POD Order Management Provider

Posted on April 6, 2026April 6, 2026 by Maddy Alcala

If you don’t get satisfactory answers to these questions, you’re likely buying tech-debt and security risks disguised as software.

1. Order Management Coverage & Tooling

Does your platform provide end-to-end order management capabilities with appropriate tooling at each stage? Specifically, can you demonstrate your capabilities in: front-end order placement integration, edge case handling and order failure resolution workflows, customer service interfaces for order modifications and re-fulfillment, and inventory/vendor integration management?

2. Performance & Scalability Under Load

What are your system’s load characteristics and resilience protocols?

How frequently do you conduct load testing?

Does your infrastructure auto-scale both horizontally and vertically?

Can you guarantee sustained processing of at least 100+ orders per second without system degradation or cascading failures to downstream systems and integrations?

3. Role-Based Access Control

Does your platform implement granular role-based permissions that allow different user types (integrations, customer service, administrators, etc.) to perform only their designated actions and tasks?

4. Compliance & Data Security

Is your platform SOC 2 compliant, and can you provide current certification documentation to verify your data security controls and practices?

If it handles Credit Card billing of some type, does it conform to PCI Standards?

5. Disaster Recovery & Business Continuity

What is your RTO (Recovery Time Objective) and RPO (Recovery Point Objective) in the event of a system failure?

Can you walk us through your disaster recovery plan, including how you handle data backup, failover procedures, and the last time you successfully tested a full system recovery?

6. API Reliability & SLA Guarantees

What are your documented API uptime SLAs, and what compensation or remediation do you offer when these are not met?

Can you provide your actual uptime metrics from the past 12 months, including any significant outages, their root causes, and resolution times?

7. Integration Flexibility & Technical Debt

How does your platform handle custom integrations beyond your standard connectors?

What is your API versioning strategy, and how much advance notice do you provide before deprecating endpoints?

Can you describe your approach to managing technical debt and legacy integration support?

8. Multi-Channel Order Orchestration & Centralized Customer Service

How does your platform handle orders originating from multiple sales channels simultaneously (e-commerce, marketplaces, mobile apps, B2B portals)?

Can you demonstrate unified inventory visibility and order management across all channels to prevent overselling?

Does your platform provide a centralized customer service interface where agents can view, manage, and modify orders from any channel in a single workspace, ensuring consistent customer experience regardless of purchase origin?

9. Mixed-Channel Order Fulfillment with Print-on-Demand

Can your system intelligently process orders containing items that need to be fulfilled from different sources within a single transaction? For example, if a customer orders three items where one ships from a warehouse, one requires print-on-demand production, and one requires drop-shipping from a vendor, can your platform coordinate this as a unified order experience?

10. Advanced Routing & Orchestration Logic

What level of sophistication does your routing engine support for complex fulfillment scenarios?

Can you configure custom routing rules based on multiple variables (inventory location, shipping speed, cost optimization, item attributes, customer proximity, vendor capacity)? Can you show examples of how your platform handles split shipments, partial fulfillments and dynamic re-routing when initial fulfillment paths fail?

The OrderMesh Fulfillment Network: The Engine Behind Scalable, Reliable Print

Posted on April 3, 2026April 6, 2026 by Maddy Alcala

For over a decade, Gooten has operated one of the largest, most diverse print-on-demand networks in the world. We’ve shipped tens of millions of items across nearly every product category, scaled into new regions, and handled nearly every fulfillment edge case you can imagine. And through that, one thing has become clear:

A print-on-demand fulfillment network is only as powerful and nimble as the software behind it.

That’s why we’ve been rebuilding our Fulfillment Network inside OrderMesh—a modern, intelligent, and scalable order management platform designed to meet the needs of today’s print-on-demand businesses.

The OrderMesh Powered Fulfillment Network

Managing print-on-demand production networks can be messy business. These networks often start with a handful of suppliers and grow organically over the course of years. The processes to manage them are often fragmented, reactive, and built on manual workflows and outdated technologies. Adding a print vendor often means starting from scratch—new rules, new integrations, new chaos. That doesn’t work at scale.

With OrderMesh, we built the software to solve that problem and we’re packaging a decade’s worth of print-on-demand network management into a single powerful fulfillment engine.

The OrderMesh Fulfillment Network is not a collection of vendors, it’s a coordinated engine designed to:

Support global scale with localized production and lower international shipping costs
Handle overflow demand and seasonality without compromising SLAs
Accelerate product expansion so you don’t lose revenue when a new category takes off
Complement or replace internal production with flexible, print-on-demand capacity
Enable test-and-learn personalization before committing to inventory
Meet marketplace standards like Amazon, TikTok Shop, and Walmart

The Fulfillment Network isn’t just about access. It’s about agility, transparency, and control.

Our long-term vision for this network is ambitious and simple: we are working to create the most intelligent, reliable, and revenue-driving POD network in the world.

Why It Matters

The need for a managed print fulfillment network isn’t hypothetical. These are the real problems we hear from customers every day:

“I need to expand into Europe without flying blind.”

“I can’t afford to miss Q4 volumes again.”

“My customer wants new products that we don’t make yet.”

“I can’t decide if we should buy a new machine or outsource.”

“We need to test demand before we go all in on inventory.”

“We can’t meet TikTok’s or Amazon’s SLAs on our own.”

OrderMesh is the software brain that powers the network engine to solve these problems. If you’re building the future of commerce, content, or print-on-demand production, this is the fulfillment network built for you.

OrderMesh: Modern Order Management Infrastructure for Print-on-Demand

Posted on March 14, 2026April 6, 2026 by Maddy Alcala

Over the last decade, Gooten has operated deep in print-on-demand: fulfilling millions of items, supporting recognizable brands, and navigating the complexity of made-to-order production at scale.

We’ve seen the pain points: brittle integrations, misrouted orders, exception overload, production blackouts, inconsistent SKU data, and hours lost to spreadsheets just to move orders from acceptance to shipment. The takeaway is simple: print-on-demand isn’t hard for businesses to use because of the printing. It’s hard because of inadequate infrastructure and technology.

That’s why we built OrderMesh.

OrderMesh wasn’t a side project for Gooten. It was the biggest bet we ever made that started in 2021.

As our fulfillment network expanded and enterprise customers demanded more flexibility and operational intelligence, our legacy Gooten systems couldn’t keep pace. We didn’t need another patch—we needed new infrastructure.

We needed something modern and API-first, with platform security rigorous enough to withstand enterprise compliance vetting. Something purpose-built for print’s complexity and a system that would make a print-on-demand expert say “this was built by someone who knows this space.”

That’s what OrderMesh delivers. It’s the most strategic investment we’ve made as a company, and it now forms the foundation for Gooten as part of Taylor Corporation.

What It Does

OrderMesh is an order management platform built for the print-on-demand supply chain. It connects brands, marketplaces, decorators, printers, and distributors, orchestrating how orders move across vendors, methods, and systems.

Dynamic routing and exception handling.

Use OrderMesh to route orders across locations, vendors, or print methods based on customer requirements, available capacity, supplier preference, performance, and more, with real-time exception management built in. If the data exists, it can inform routing in OrderMesh.

Plug-and-play integrations.

Our growing ecosystem of vendor plugins, platform connectors, and open APIs makes it straightforward to manage fulfillment networks and connect sales channels without engineering bottlenecks. Make OrderMesh the last vendor integration you ever need with self-serve vendor onboarding features and a developer environment built for print.

Product normalization and catalog control.

OrderMesh normalizes catalog data across producers, creating a single source of truth and making multi-node vendor networks functional. The print-on-demand industry lacks data standards and the OrderMesh team is keen to solve this problem.

Operational visibility.

Every order is traceable. Monitor margin, SLA, throughput, facility performance—all tracked and visible.

Whether you’re a brand running your own supply chain, a marketplace connecting buyers and producers, or a manufacturer in-need of internal order management tooling, OrderMesh can work for you and replace clunky legacy systems with modern, reliable technology. OrderMesh is SOC 2 compliant from the ground up and your data is your data with the right to be forgotten. Reliability, security, and data integrity aren’t optional for the OrderMesh team and they shouldn’t be for your business either.

Where Gooten Fits In

OrderMesh doesn’t replace Gooten—it expands what Gooten can do.

Our Fulfillment Network now operates within the OrderMesh platform. You still access our production partners, but with better tooling and transparency. That means a fulfillment network ten times larger and truly global. A catalog expanding from hundreds of thousands of SKUs to millions. More integrations, more routing flexibility, fewer bottlenecks. Expansion beyond print-on-demand into new fulfillment strategies and production types.

Gooten can act as a “vendor” for your business through this Fulfillment Network, but the power of OrderMesh is the tooling that gives you the ability to transact directly with print-on-demand suppliers as well. You own the commercial relationships; we’re just the software layer that makes it easy to do business.

OrderMesh already powers some of the most complex operations in print. If you’re ready to see what it can do for yours, reach out at ordermesh.com.