Most people searching Celonis competitors want one of two things: a cheaper way to see where their processes leak, or something that actually fixes the leak. Celonis does the seeing, and does it very well. We think most manufacturers and wholesalers already know where the waste sits, and need agents that do the work instead.
Ask an operations director at a 200-person wholesaler where their process breaks and you rarely get a shrug. You get a name, a desk and a number: two people in internal sales retyping emailed orders into Business Central, every morning, before ten. Nobody needed an event log to find that. This article sets out what Celonis is genuinely good at, where it stops, and how to tell which of those two problems you actually have.
We build the second thing. Lleverage runs AI agents that read the order, the invoice or the quote request, apply your rules and post the result into your ERP, which is the order-to-cash work that sits underneath most of these questions. If you want to see the difference rather than read about it, book a demo and bring one of your own documents.
What does Celonis actually do?
Celonis is a process intelligence company. It reconstructs how work really flows through your systems by reading the event logs those systems leave behind, then shows you the difference between the process on the whiteboard and the process in reality: the reworks, the maverick approvals, the orders that bounce between three people before anyone touches them.
The core asset is what Celonis calls the Process Intelligence Graph, a system-agnostic model that extracts and standardises process data from any source. On top of it sit Process Copilots and the AgentC suite. Celonis positions the whole thing as "The Context Model", described on its own homepage as the missing piece of an enterprise AI stack.
That framing matters more than it first appears, and it is the honest heart of this comparison. Celonis's own agent strategy is not to run your processes. AgentC, launched at Celosphere in October 2024, exists to feed process context to agents built somewhere else: its Process Intelligence API shares metrics and recommended actions with Microsoft Copilot Studio, Amazon Bedrock Agents, IBM watsonx Orchestrate, Salesforce Agentforce and open-source environments like CrewAI. Celonis makes other people's agents better informed. It is a context layer by design and by its own account, not an execution layer.
The company has been building this since 2011 and the analyst record is strong: a Leader in The Forrester Wave for Process Intelligence Software in Q3 2025, and a Leader in the Everest Group PEAK Matrix for process mining for a seventh consecutive year according to its own newsroom. In May 2026 Celonis announced the acquisition of Ikigai Labs to add AI decision intelligence, with MIT taking an equity stake in exchange for a patent licence. This is a serious company solving a real and difficult problem.
What does Lleverage actually do?
Lleverage builds AI agents that carry out back-office work end to end. An agent receives the document as it arrives, whether that is a PDF attached to an email, an Excel sheet with the customer's own column names, or an EDI message, reads it, applies the customer-specific rules, and writes the finished record into Dynamics 365 Business Central, SAP or whatever system of record you run.
There is no event log involved, because the work being automated mostly never reached a system in the first place. That is the point. An emailed order sitting in a shared inbox for forty minutes leaves no trace in your ERP until a person types it in, so the delay is invisible to any technique that mines what your systems recorded.
Where Celonis produces a diagnosis, an agent produces a completed transaction. Topa Bathroom Products now has over 90% of incoming orders processed straight into Business Central by an agent, with order confirmations back to the customer inside 30 seconds and four FTEs moved off manual entry onto after-sales and service planning. At Xpol, roughly 20 minutes of manual handling per large order disappeared across about 150 orders a week, with 25 customer-specific rulesets encoded into the agent rather than left in the heads of senior staff.
"We had four and a half people — about 3.8 full-time equivalents — sitting there all day long, manually entering every single order into our Business Central ERP." – Bryan van Ingen, Operations Director, Topa Bathroom Products
Read that quote again with the comparison in mind. Bryan did not need a process model to know where his money was going. He needed the typing to stop.
Celonis vs Lleverage: how do they compare?
| Celonis | Lleverage | |
|---|---|---|
| Category | Process intelligence and process mining | AI agents that run back-office processes |
| What you get | A diagnosis: where work deviates, stalls and costs money | A finished transaction: the order, invoice or quote in your ERP |
| Data it needs | Event logs extracted from ERP, CRM and other systems of record | The document itself, plus your ERP master data |
| Handles email, PDF and Excel work | Not its purpose: that work leaves no event log | Yes, this is the primary input |
| Agent approach | AgentC supplies context to agents built in Copilot Studio, Bedrock, watsonx Orchestrate or Agentforce | The agents are the product and execute the work |
| Typical buyer | Global process owner or process excellence lead | Operations director or MD |
| Company size it fits | Large enterprise with many systems and process variants | 50 to 3,000 people, usually one or two ERPs |
| Published pricing | None published | From €2.000 per month per agent, listed on the pricing page |
| Time to first result | A mined process model, then a change programme to act on it | One process live, then the next |
Two rows deserve a caveat. Celonis not publishing pricing is normal for enterprise process intelligence and says nothing about value; it does mean you cannot budget without a sales conversation. And "time to first result" is not a like-for-like race, because the two products are finishing different races.
Why do people search for Celonis competitors?
In our experience the search splits three ways, and only one of those searchers actually wants another process mining product. Some are looking at the cost of an enterprise process intelligence programme against a back office of forty people and concluding the maths does not work. Some have run a mining project, got the heat map, and discovered that the report was the easy part. The rest were never in the market for mining at all; they typed the biggest name in process automation into a search box because their orders arrive as email attachments and somebody said AI could help.
If you are in the first or third group, the honest answer is that a Celonis alternative is not what you need. You need something that does the work. If you are in the second group, you have the most expensive version of the problem: a correct diagnosis and no mechanism to act on it.
When is Celonis the right choice?
Celonis is the right choice when you genuinely do not know where the problem is, and the reason you do not know is scale. Fifteen thousand people, four ERPs from three acquisitions, a purchase-to-pay process that runs differently in every country, and a boardroom argument about whether the delay is procurement's fault or finance's. Nobody can answer that from memory, and an event log can.
It is also the right choice when the value is in the argument itself. A mined process model is evidence. It settles disputes between functions that have been trading anecdotes for years, and it gives a programme director the numbers to defend a budget. That is worth real money in an organisation large enough to have the dispute.
We would add one condition. Buy the diagnosis when you have already decided how you will act on it, and who will. The failure mode we see is not a bad process model. It is a good one that lands in an organisation with no capacity to change anything it revealed.
When does an SME need agents instead of process mining?
When the constraint is hands, not knowledge. The test we use is blunt: can your operations director name the three worst manual jobs in the building, off the top of their head, right now? If yes, you do not have a visibility problem, and buying visibility will confirm what they said at considerable expense.
There is a second test that catches more companies than the first. Ask where the work actually happens. If the answer is Outlook, Excel and a shared inbox, process mining has very little to read, because those applications are not the system of record and the delay never becomes an event. J. Kisch & Zonen cut repetitive customer questions by 80% with an agent handling the recurring ones; none of that traffic was visible in an ERP event log, because it was email. The same is true of the document work that never reaches your ERP in the first place.
For companies in this position, our reading is that you skip the mining step entirely and start with the process you already know is broken. Take the order desk, or supplier invoices, put an agent on it, and measure what changed. You will learn more about your process from automating one part of it than from a model of all of it, and you will have the time back either way.
Can you use Celonis and Lleverage together?
Yes, and in a large enough company it is the sensible arrangement rather than a compromise. Celonis tells you which of your forty variants of order entry is costing the most and where the exceptions cluster. Agents then take over the specific steps that turned out to be manual, repetitive and rule-governed. Diagnosis feeds execution, and Celonis's AgentC direction is explicitly built for handing context to execution layers.
The reason we still frame this as "vs" is that most companies asking the question cannot afford both, and have to pick which problem to spend on first. If you are one of them, spend on the one you can prove. A process model proves nothing until someone acts on it, whereas an agent that has taken over your order intake either works or it does not, and you will know inside a month.
What should you ask before choosing either?
Four questions separate the two cases faster than any feature list, and they are worth asking out loud in the room rather than in a scoring matrix.
- Can we name our three worst manual processes today, without new analysis? A yes points at execution.
- Where does the work live: in our ERP, or in email and spreadsheets around it? Event logs only see the former.
- If a model told us exactly where the waste was, who would fix it, and with what budget? No answer means the diagnosis will sit on a shelf.
- Do we have one system of record or five? Genuine multi-system sprawl is the case process mining was built for.
Our position, stated plainly: below roughly 3,000 people with one or two ERPs, execution beats diagnosis almost every time, because the diagnosis is already sitting in your operations director's head for free. Above that, and especially across many systems, the diagnosis stops being obvious and starts being worth paying for. The company brain that stores your rules and exceptions is what makes the execution side repeatable once you start, and it is why the second agent is always faster than the first.
Frequently asked questions
Is Celonis a competitor to Lleverage?
Only partly. Celonis does process intelligence: it models how work flows and shows where it breaks. Lleverage runs AI agents that carry out the work itself. They compete for the same automation budget and often the same meeting, but they solve different halves of the problem and can be used together.
Does Celonis automate processes or just analyse them?
Celonis analyses processes and supplies context to automation built elsewhere. Its AgentC suite shares process context through an API with agents developed in Microsoft Copilot Studio, Amazon Bedrock Agents, IBM watsonx Orchestrate and Salesforce Agentforce. The execution happens in those environments, not inside Celonis itself.
How much does Celonis cost?
Celonis does not publish pricing; figures come from a sales conversation and vary with data volume, connected systems and scope. Lleverage publishes its pricing: one monthly price per agent, starting from €2.000 per month, with integration and AI usage included rather than billed separately.
Do we need process mining before automating with AI agents?
Usually not, in companies under a few thousand people. If your team can already name the worst manual jobs, mining will confirm what they told you. Start with one known process, automate it, measure the result, and use what you learn to choose the next one.
What are the main Celonis competitors in process mining?
The closest products by category are SAP Signavio, Software AG's ARIS, Microsoft Power Automate Process Mining, UiPath Process Mining and Skan AI. Lleverage is not one of them, because it executes work rather than modelling it. Choose from that list only if a diagnosis is genuinely what you need.
Start with the process you already know is broken
If your order desk retypes emailed orders every morning, you do not need a study to tell you so. Bring one of those emails, one of those spreadsheets, or one of those supplier invoices to a demo, and we will run an agent against it while you watch. That is a faster answer than any comparison page, including this one.
Book a demo with Lleverage and see what an agent does with your own documents. If it turns out you really do have a multi-system visibility problem, we will say so.