At a glance
| Dimension | Pilaro | Celonis |
|---|---|---|
| Primary proposition | AI-first execution and steering | Process Intelligence platform to industrialize Enterprise AI |
| Core truth layer | Organizational task/value-stream model plus execution evidence | Context Model / Process Intelligence Graph: dynamic operational digital twin |
| Discovery | People-first task discovery and confirmation, organizational context, systems/data readiness | Process mining, object-centric process data, task mining, desktop actions, business knowledge and other operational context |
| Analyze | Work, context, bottlenecks, handoffs, AI readiness | Deep process analysis, patterns, conformance, simulation, predictions and what-if scenarios |
| Design | Future value stream, phases, tasks, responsibilities, AI execution modes | Process Designer, outcomes, guardrails, workflows and AI insertion points |
| Operate | Pilaro execution model plus connected execution environments | Orchestration Engine coordinating agents, humans and systems in real time |
| Human/AI model | Explicit Manual → Assisted → Orchestrated → Delegated Skill Shift | Explicit AI insertion points, human-in-loop and orchestration; no equivalent public Skill Shift model identified |
| Strategic context | Objective → KPI → Value Stream → Task | Context Model includes business knowledge, organizational goals and decision intelligence |
| Prediction | Pilaro labels predictions/recommendations as future direction where applicable | Celonis has simulations and predictive capabilities; Prediction Builder was announced in private preview in 2026 |
| Industry focus | Physical-product value networks | Horizontal enterprise with major supply-chain/manufacturing depth |
What Celonis does today
Celonis’ current platform is one of the strongest signals that process intelligence and process orchestration are converging.
The Context Model
Celonis combines process data, business knowledge and intelligence into a living operational context layer. Its 2026 Context Model builds on the Process Intelligence Graph and is intended to give humans and AI agents a richer understanding of how the business operates. Celonis:NEXT 2026.
Analyze
Celonis uses process intelligence to show how processes actually run, identify bottlenecks and opportunities, find strategic AI use cases, and support simulation and predictive analysis. Celonis Analyze.
Design
Celonis now includes process design capabilities for creating a target operating state, defining workflows, outcomes, guardrails and where AI should participate.
Operate
The Orchestration Engine is a generally available part of the platform that coordinates AI agents, humans, automations and systems in real time. Celonis Operate.
External agent context
Celonis also exposes process context and tools to external agents using MCP, strengthening its position as an operational-context layer for enterprise AI.
Where the platforms overlap
The overlap is now extensive:
- understand how work actually happens;
- identify where AI will create business value;
- redesign the target process rather than bolt AI onto the old process;
- define where people and AI should participate;
- orchestrate processes across humans, agents and systems;
- connect process performance to business outcomes;
- continuously improve based on operational evidence;
- provide enterprise context to AI agents.
A simplistic page saying “Celonis mines; Pilaro runs” would be wrong in 2026.
Where Celonis is stronger today
1. Operational data and process intelligence
Celonis has a deep, mature platform for extracting and interpreting process data across enterprise systems. Its object-centric process model and Process Intelligence Graph provide a sophisticated operational digital twin.
2. Process mining and conformance
Celonis can reconstruct large-scale operational patterns from system data and identify deviations, bottlenecks and cross-process relationships that would be extremely difficult to reproduce manually.
3. Enterprise data connectivity and context
The platform is built to ingest large volumes of heterogeneous enterprise operational data and enrich it with business context.
4. Process simulation and intelligence
Celonis has mature analytical tooling and is pushing into forecasting and decision intelligence. Where a company already has rich event/system data, this is a formidable advantage.
5. Established process-improvement footprint
Celonis has a large installed base and longstanding process-improvement credibility, particularly in areas such as procurement, order-to-cash, accounts payable, supply chain and ERP-centric operations.
Where Pilaro approaches the problem differently
1. Pilaro begins with people before instrumentation is complete
Pilaro can begin by helping an individual articulate and confirm their own tasks, outcomes, information, systems and responsibilities. That matters in knowledge work where critical activity is not yet reliably visible in ERP/CRM event data.
Celonis has Task Mining and increasingly combines system, desktop and unstructured context, so the distinction should not be stated as “Celonis cannot see human work.” The difference is the product interaction and governance model: Pilaro makes people’s explicit confirmation and permission part of creating organizational truth.
2. Skill Shift is a visible transformation model
Pilaro treats the evolving split between human and AI contribution as something the organization should design and measure task by task:
Manual → Assisted → Orchestrated → Delegated.
Celonis supports AI insertion points and human participation, but Pilaro makes the evolution itself a user-facing organizational model.
3. Pilaro connects individual, team and leadership perspectives in one hierarchy
Pilaro’s public model is explicitly:
Objective → KPI → Value Stream → Task.
That allows the same task discovered by an individual to become part of a team value stream and ultimately part of the execution evidence leadership can steer from.
Celonis’ Context Model increasingly includes organizational goals and decision intelligence, so this is not an “Celonis has no strategic context” argument. The difference is that Pilaro’s hierarchy is the central operating-model experience from the individual upward.
4. Pilaro prepares the human/AI execution itself
Pilaro’s public execution story includes task-aware support: task, context, skill, prompt/model guidance and quality checks in the AI environments where people work. That is different from using process context primarily to power enterprise agents and orchestrations.
5. Physical-product value networks are the product lens
Celonis has very strong manufacturing and supply-chain capabilities, but remains a horizontal enterprise Process Intelligence platform. Pilaro’s entire public information architecture starts from suppliers, manufacturers, brand owners and own-brand retailers and the work that moves a physical product through that network.
Which may fit better?
Celonis may fit better when:
- you have rich ERP/transaction/process data and want an operational digital twin;
- process mining, conformance, object-centric analysis and systemic bottleneck detection are priorities;
- you want to ground enterprise AI in a mature Process Intelligence Graph;
- you need to analyze and optimize large cross-system operational processes at enterprise scale;
- you already use Celonis and want to extend from process intelligence into orchestration and AI.
Pilaro may fit better when:
- much of the critical work still lives in people’s heads, documents, conversations and personal AI tools;
- you want individuals to participate directly in discovering and confirming their work;
- the organizational problem includes changing roles and skills, not only changing process flows;
- Skill Shift between human and AI needs to be explicit per task;
- you want a common experience connecting individual work to team value streams and leadership objectives;
- your core transformation is in a physical-product value network.
Can Pilaro and Celonis work together?
Architecturally, yes, and the combination is potentially interesting.
Celonis could provide high-quality operational process intelligence from system data while Pilaro provides a people/task-centric operating model around work discovery, Skill Shift and organizational activation.
Execution evidence and system events could strengthen both views.
Do not claim an integration until one exists. Present this only as an architectural possibility.
FAQ
Is Celonis still mainly process mining?
No. Its 2026 platform explicitly spans Analyze, Design and Operate and includes an Orchestration Engine for humans, systems and AI agents.
Which comparison is closest to Pilaro?
Of the six vendors in this program, Celonis has the broadest conceptual overlap because it now combines process discovery/intelligence, redesign, AI context, orchestration and continuous improvement.
What remains genuinely different?
Pilaro’s strongest distinctive concepts are people-permissioned bottom-up task discovery, Skill Shift as a first-class human/AI operating model, and an individual-to-team-to-strategy hierarchy designed around AI-first execution.
Does Celonis understand strategic goals?
Increasingly, yes. Its Context Model includes business knowledge and organizational goals, and its process design can begin from desired outcomes. Do not claim otherwise.
Which has stronger process intelligence today?
Celonis. That is its established category and one of its deepest technical assets.