Process Intelligence in B2B Commerce: From Insight to Order
Most manufacturers and wholesalers already know where their orders go wrong. A process intelligence dashboard shows that checkouts stall when an item is out of stock, that quotes wait days for a pricing approval, and that a share of orders comes back from the ERP for manual correction. The analysis is accurate. By the time anyone acts on it, though, the buyer who abandoned the cart has often ordered from someone else, and the improvement project is still waiting for budget.
That gap between knowing and acting is where the value of process intelligence is won or lost in commerce, and it is the gap behind the integration Emporix and Celonis announced on 20 October 2026. The planned integration is designed to make knowledge from business processes usable in order processing: the Celonis Context Model is to give Emporix ACE live knowledge of how operations really run, so that Emporix can act on it inside the order itself. This post looks at what that changes for operations and commercial leaders, where the approach fits today, and what to check before you connect process intelligence to the order itself.
Get the study The Autonomous Commerce Shift 2026: the full results from 500 B2B leaders in DACH on how much of their commerce still runs by hand. Download the study
What Process Intelligence Shows, and Where Commerce Has to Pick It Up
Process intelligence shows how a business really runs, using data from the systems it already has, and it is the most reliable way to find where orders stall and why. In commerce, that knowledge pays off fully only when it reaches the systems that run the order, while the customer is still buying.
Process intelligence is the practice of reading event data from systems such as ERP, CRM and the online shop, linking it to business context, and building a live model of how processes actually run, including where they stall, loop back or depend on manual work. It tells a business what is happening and why, as the basis for decisions and action.
At the heart of the Celonis Platform is the Celonis Context Model, which creates a living digital twin of business operations from process data, business knowledge and decision intelligence. According to the announcement, it captures data from a wide range of source systems and links it with business context, which gives an objective view of real operations and their dependencies. For an order-to-cash process, that view is valuable. It can show that one product family causes most abandoned checkouts, that orders from a particular customer group need manual price corrections, or that substitutions are agreed by phone but never recorded.
The bottleneck usually sits on the commerce side, not in the analysis. Most commerce systems were not built to receive that kind of knowledge and act on it while an order is open, so the insight travels through meetings, tickets and release cycles before it changes anything a customer sees.
The Last Mile Problem: Why Order Issues Get Fixed After the Customer Has Gone
In B2B commerce, most order problems have to be solved inside the transaction: while the cart is open, the quote is pending or the order is waiting for confirmation. Improvement projects work on a timescale of weeks or months. That mismatch explains why so much manual work survives in processes that companies already understand well.
Emporix's own research shows the size of the gap. In the study The Autonomous Commerce Shift 2026, which covered B2B companies with 250 or more employees in five DACH sectors, 47 percent of suppliers rate themselves as largely automated. At the same time, 59.6 percent say manual work still accounts for more than a quarter of their commerce processes, and only 2.4 percent have reduced the manual share below 10 percent (Emporix, 2026). The pattern behind those numbers is that companies measure digital touchpoints rather than whether a process completes without manual intervention.
Two familiar responses fill the gap today. The first is people: inside sales or customer service picks up the exception, calls the buyer and offers an alternative. It works, but it is expensive and depends on someone noticing in time. The second is hard-coded automation, such as a rule that always proposes product B when product A is out of stock. It is fast, but it treats every customer the same, and every change to the rule becomes an IT ticket.
| Insight handed over manually | Insight connected to commerce execution | |
|---|---|---|
| When the problem is found | In analysis, after the fact | While the order is still open |
| Who acts | A person, or an improvement project | The commerce process, with people handling the exceptions |
| What the customer sees | Nothing, or a call days later | A suitable option in the checkout, portal or quote |
Emporix and Celonis: From Process Analysis to Transactional Execution
The partnership places Emporix in the Operate phase of Celonis's continuous cycle of Analyze, Design and Operate. The Context Model shows where a process runs poorly, the process is redesigned, and the redesigned process then has to run somewhere. For transactional processes such as orders, quotes and portals, that is the role Emporix ACE plays in the partnership.
Emporix is an Autonomous Commerce Execution® platform for B2B manufacturers and wholesalers. Autonomous Commerce Execution is an operating model in which commerce processes observe, decide and act across the systems a business already runs (ERP, pricing, inventory, fulfilment and service) without waiting for a human to trigger each step. People stay in the loop for the decisions that need judgement. Emporix ACE is the platform that delivers it.
Why Transactional Execution Runs on Emporix
Emporix fits this role because of how the platform is built. It comes from high-volume B2B commerce, so it is built for transaction volume and low latency, acts as the system of record for execution, and is composable by design: applications are shaped around the customer's process instead of forcing the process into a fixed template. AI agents carry out process steps, and the platform follows a prompt-first approach, aimed at letting teams change how a process runs without starting a development project for every adjustment.
Emporix ACE does not depend on Celonis to act. Its processes already observe, decide and act across ERP, pricing and inventory. What the Celonis Context Model adds is a far deeper view of how operations really run, so the decisions ACE takes are based on the whole business rather than on what the commerce system alone can see.
"With Celonis, we bring the relevant information directly into the sales process. Emporix coordinates the response, shows the customer a suitable option and processes their order," says Mark Holenstein, CEO of Emporix.
From Insight to Order: The Out-of-Stock Example
The announcement illustrates the planned integration with an out-of-stock example. It shows the direction of the partnership rather than a capability every customer can switch on today:
- Analyze: the Celonis Context Model recognises that many checkouts are abandoned because a product is unavailable.
- Design: a response is defined, in this case offering affected customers a suitable substitute product.
- Operate: Emporix ACE shows the customer that option and, if they accept, processes the order.
What separates this from a fixed substitution rule is the context behind it. A rule proposes the same alternative to every customer until someone rewrites it. With the Context Model behind the decision, the response can reflect what is actually happening in operations, such as which products are causing abandoned checkouts and for whom. The coordination in the middle is commerce orchestration: the coordination layer that runs decisions and handoffs across commerce, ERP, CRM and fulfilment systems, so a process moves on its own instead of waiting for someone to carry it between tools. Integration connects systems; orchestration runs the process across them. If you want to see how Emporix handles that layer, the page on commerce orchestration explains it.
In Emporix, processes like this are built as Value Streams. A Value Stream is a pre-built, configurable business process that connects customer journeys, internal workflows and data across systems, from the trigger to the outcome, for example from an incoming PDF purchase order to a confirmed order in the ERP. Business teams adapt Value Streams in a no-code modeler rather than through development projects. This explainer on how Value Streams run commerce operations goes into the mechanics.
Return on AI (RoAI) Depends on Context at the Point of Decision
AI investments pay back when they change a decision inside a live process. Without business context, an AI agent in commerce can only follow fixed rules or guess. With context, it can choose an option that fits the customer, the stock position and the state of the process, and that is the difference between a pilot and a measurable result.
Celonis makes the same argument. "For companies to achieve measurable RoAI, they need the relevant business context for their AI applications. The Celonis Platform delivers exactly that. Through the integration with Emporix, interruptions in the ordering process can be resolved autonomously and in a targeted way, in real time," says Alex Rinke, co-founder and co-CEO of Celonis (translated from the German announcement).
This is where Agentic Commerce Intelligence comes in. Agentic Commerce Intelligence refers to AI agents embedded inside commerce processes that interpret inputs, make bounded decisions and take actions, such as reading an order email, proposing a substitute product or routing an exception, within rules the business sets. For a managing director or COO, the useful question is therefore less about which AI features a platform lists, and more about where the AI gets its context and what it is allowed to do with it.
Where a process is well defined, the result can be measured. ACR, a North American supplier of packaging and prep products, reports 87 percent faster order processing with Emporix, as described in the ACR customer story. Context from process intelligence is what can extend that kind of result to the judgement-heavy moments, such as an out-of-stock checkout, where a fixed rule does not know which alternative a particular customer will accept.
Extending the Running System by Prompt, Without a Second Platform
The second part of the announcement deals with a different cost: business models that do not fit a standard commerce setup. Emporix demonstrated how companies can extend their existing system with new applications described in natural language, using their existing product and order data and their own data objects, without replacing the platform.
The example in the release comes from construction equipment rental. Specialist equipment such as drills or concrete breakers does not fit a standard product catalogue, because the rental period, availability and the inspection on return matter more than a unit price. In the demonstration, a prompt produces an application that models this rental business inside the running system. To support this, the platform provides an interface for AI agents, a shared knowledge base and prebuilt agents.
"Companies can extend the running system with additional applications by prompt, without switching their platform," says Mark Holenstein.
For leaders, this addresses one of the most common fears in a platform decision: backing a system that cannot follow the business when it adds a rental, service or subscription model. In the past, each new model tended to mean a second system or a custom development project. Being able to extend the system that already runs the orders keeps data, processes and governance in one place. Our post on why AI in B2B sales needs business context shows the same prompt-first approach applied to sales cockpits.
Five Questions to Ask Before Connecting Process Intelligence to Commerce
Connecting process intelligence to commerce execution is a governance decision as much as a technology one. These five questions help leaders judge whether the approach fits their operation and where to start:
- Which order problem costs you the most, and can you see it in your data today? Abandoned checkouts, delayed quotes and manual order corrections are typical candidates. Start with one.
- Where is the decision made today, and how long does it take? If the answer is "in a weekly meeting", the gap between insight and action is your business case.
- Which decisions may the process take on its own, and which need a person? Proposing a substitute is a different level of risk from changing a contract price. Set the boundaries before you automate.
- Is the data behind the decision reliable? A substitute offer is only as good as the stock figures and customer master data behind it. Process intelligence will expose weak data quickly; plan for that.
- How will you measure the return? Agree the measure before you start: recovered orders, substitute acceptance, manual touches or order cycle time, measured before and after.
There are honest limits. The integration is starting with a first group of customers and will grow over the coming months, so a realistic plan starts with one process rather than a programme. Acting on process knowledge inside the order also needs an owner on the business side who is accountable for the rules the process acts on. For a broader view of the operating model, see what autonomous B2B commerce execution looks like in practice.
Frequently Asked Questions About Process Intelligence and Emporix
What did Emporix and Celonis announce?
On 20 October 2026, Emporix announced an integration with the Celonis Platform that connects the Celonis Context Model to Emporix ACE, its Autonomous Commerce Execution platform. The Context Model is to supply live knowledge of how operations run, and Emporix to execute the resulting transactions at volume. The goal is that problems in the order process are resolved while the order is still open.
What is the difference between process intelligence and process mining?
Process mining reconstructs how a process actually runs from the event logs of systems such as ERP and CRM. Process intelligence, the category Celonis leads, builds on that by linking process data with business knowledge, so a company understands not only where a process deviates but why, and what that means for decisions. In commerce, the next step is to connect that understanding to the systems that run the order.
Do we have to replace our ERP or commerce platform to use this?
No. Emporix ACE works across the systems a business already runs, such as ERP, pricing, inventory and fulfilment, and the Celonis Context Model draws its data from those source systems. Emporix also demonstrated how companies can extend the running system with new applications by prompt, without switching their platform. That makes the approach an addition to an existing IT estate rather than a replatforming project.
Who stays in control when the order process acts on its own?
The business does. AI agents in Emporix ACE make bounded decisions within rules the company sets, and people stay in the loop for the decisions that need judgement. A sensible setup lets the process handle clear cases, such as offering a substitute for an unavailable product, and routes higher-risk decisions, such as price changes or contract exceptions, to the responsible team.
When can we use the Emporix and Celonis integration?
The integration is starting with a first group of customers, with the Celonis Context Model as its foundation and further capabilities following over the coming months. Whether it fits your business now depends on the processes and systems involved, so the best next step is a conversation with the Emporix team about the order problem you want to solve first.
Process Intelligence Pays Back When It Reaches the Order
Process intelligence has given B2B companies a clear picture of where their orders break. The next advantage goes to the companies that act on that picture while the customer is still in the process, not in the next project cycle. Those that connect one well-chosen process to commerce execution now will have the data and governance in place as more decisions move into the process itself.
The quickest way to judge the fit is to see your own catalogue and order process running on Emporix ACE. Share your website and the order problem you want solved, and the Emporix team builds a personalised demo on the platform in a few hours, then walks your team through it in 30 minutes. Prefer a conversation first? Talk to an Emporix expert.
