Top 10 Process Intelligence Platforms 2027
In our view, the best process intelligence platforms for 2027 are Noreja, Celonis, SAP Signavio and Pega – followed by ARIS, UiPath, ServiceNow, Appian, Skan AI and iGrafx. Since Gartner renamed its Magic Quadrant from “Process Mining Platforms” to “Process Intelligence Platforms” in May 2026, the process map alone no longer decides: what counts is whether a platform delivers context, feeds AI agents and turns insights into action. The list reflects the state of October 2026 and looks ahead to what will matter in 2027.
Updated October 2026 · Published by Noreja · Methodology disclosed
The Top 10 at a Glance
| Rank | Solution | Best for |
|---|---|---|
| 1 | Noreja | Causal analysis with AI context |
| 2 | Celonis | Large enterprise transformation programs |
| 3 | SAP Signavio | SAP-centric process landscapes |
| 4 | Pega Process Mining | Mining tied to app redesign |
| 5 | ARIS | Governance and model conformance |
| 6 | UiPath Process Mining | Discovery that feeds automation |
| 7 | ServiceNow Process Mining | Service and ITSM processes |
| 8 | Appian Process HQ | Low-code orchestration with mining |
| 9 | Skan AI | Making desktop work visible |
| 10 | iGrafx Process360 Live | Modeling, simulation and repository |
How We Ranked
Context and knowledge model
How well does the data model connect events, business objects, relationships and enterprise knowledge? The richer the context, the more reliable the analysis and the sounder the foundation for AI.
Analytical depth
Does the platform explain causes, or does it mainly show frequencies and sequences? What matters is whether deviations are classified in business terms and causes are traceably evidenced.
AI and agent readiness
Can assistants and agents access the process context – internally or through open interfaces such as the Model Context Protocol – and do their recommendations remain verifiable?
Path to action and openness
How quickly do insights become actions, and does that work without tying the analysis to a single ERP, RPA or platform ecosystem?
Transparency note: this ranking is published by Noreja, and Noreja is part of the list. The criteria above are disclosed and structurally favor causal, graph-based approaches. Information on other vendors is based on publicly available sources (as of October 2026); feature scope and packaging change frequently – the respective vendor’s documentation is authoritative. Trademarks belong to their respective owners.
The Top 10 in Detail
Noreja
Best for: Causal analysis with AI context
Noreja treats process intelligence as a context layer: events, business objects, relationships and enterprise knowledge live in an Event Knowledge Graph on which the platform analyzes processes causally and temporally. The AI assistant Minerva reads this graph and the knowledge in the Context Hub – with local or cloud models – and makes causes and recommendations traceable.
- Event Knowledge Graph as an extensible knowledge base for analysis and enterprise-specific AI
- Minerva Agent Library with ten specialized analysis agents, plus continuously running Frontier Agents
- Source-system agnostic, free choice of LLMs up to on-premises, and publicly available pricing
Keep in mind: Actions are executed through connected systems – Noreja does not replace a workflow or RPA platform, and reliable results require clean timestamps and identifiers.
Celonis
Best for: Large enterprise transformation programs
Celonis shaped the market and is positioned as a Leader in the 2026 Magic Quadrant for Process Intelligence Platforms. The platform combines a Process Intelligence Graph with an Orchestration Engine for automated follow-up actions; through AgentC and an MCP server, Celonis also makes process knowledge available to external agent platforms.
- Largest selection of pre-built connectors and an extensive library of process apps
- AgentC connectivity to agent platforms, including Copilot Studio, Bedrock and Agentforce
- Mature training and enablement programs for building internal teams
Keep in mind: Model construction relies on directly-follows frequencies, and the first reliable analysis is usually preceded by labor-intensive data extraction.
SAP Signavio
Best for: SAP-centric process landscapes
SAP Signavio combines modeling, process mining, governance and benchmarks in one suite and, according to SAP, is a Leader in the Gartner Magic Quadrant for the fourth consecutive year. Joule Agents for SAP Signavio have been generally available since February 2026, supporting content discovery, process analysis, value cases and onboarding.
- Largely pre-configured connectivity to SAP source systems
- End-to-end suite from modeling through mining to conformance
- Industry benchmarks for putting your own metrics in context
Keep in mind: Its full value unfolds primarily in SAP-dominated landscapes; heterogeneous non-SAP sources require additional integration effort.
Pega Process Mining
Vendor: Pegasystems
Best for: Mining tied to app redesign
Pega is positioned as a Leader in the 2026 Magic Quadrant for Process Intelligence Platforms and combines process mining, task mining and process modeling in one platform. According to the vendor, mined insights feed into Pega Blueprint, where processes are simulated, optimized and turned into reworked workflows and applications.
- Process mining, task mining and modeling in one platform
- Short path from analysis to redesign via Pega Blueprint
- Positioned as operational context for deciding where to deploy AI agents
Keep in mind: The path from insight to execution is geared toward the Pega platform – in heterogeneous execution landscapes, the integrations deserve a close look.
ARIS
Best for: Governance and model conformance
ARIS combines its long BPM heritage with process mining and AI and, according to the vendor, is a Leader in the Gartner Magic Quadrant for the fourth consecutive year. With Process Core, ARIS maintains a governed digital twin of processes, roles, rules and controls that is also meant to serve as guardrails for AI agents.
- Tight coupling of process mining with a governed model repository
- Automated conformance against to-be models in BPMN and EPC
- AI-supported root-cause miner correlating delay factors
Keep in mind: Root-cause analysis remains correlative, and the full value emerges in conjunction with the ARIS BPM suite.
UiPath Process Mining
Best for: Discovery that feeds automation
UiPath connects process mining and task mining with its automation platform. With Maestro, UiPath orchestrates agents, robots and people in BPMN processes – making process intelligence the starting point for agentic automation and for measuring its results.
- Combined view of system, desktop and communication data
- Maestro coordinates agents, robots and people in BPMN processes
- Integrated governance and ROI tracking for automation initiatives
Keep in mind: Discovery is primarily geared toward finding automation candidates; the full value emerges together with the UiPath platform.
ServiceNow Process Mining
Best for: Service and ITSM processes
ServiceNow Process Mining runs natively on the Now Platform and analyzes service workflows without external data extraction. With the Zurich release, process and task mining sit in the context of agentic AI; external data is surfaced via Workflow Data Fabric, primarily for workflows and agents.
- No external data extraction needed for ServiceNow processes
- Real-time KPI monitoring for SLA compliance
- Insights flow directly into workflows and agents on the same platform
Keep in mind: Mining analysis stays focused on platform processes; end-to-end flows across ERP and back-end systems lie outside its core.
Appian Process HQ
Best for: Low-code orchestration with mining
Appian Process HQ bundles data fabric, process mining, machine learning and the AI Copilot in a guided analysis environment. Insights can be translated directly into orchestrated workflows and case management on the same low-code platform.
- Short path from insight to orchestrated implementation
- Low-code development for rapid process changes
- Orchestration of complex workflows across multiple systems
Keep in mind: Mining is a building block of the orchestration platform rather than its methodical core; a causal, graph-based process model is not part of its scope.
Skan AI
Best for: Making desktop work visible
Skan AI observes work directly on the desktop: screen content is processed locally, and only anonymized metadata reaches the analytics platform. The portfolio is split into Blueprint, Intelligence and Agents; in February 2026 Skan introduced the Agentic Ontology of Work, an open semantic framework for how humans and AI agents work together.
- Also captures work in applications that provide no usable event logs
- Honorable mention in the 2026 Magic Quadrant and Representative Vendor in the Gartner Market Guide for Task Mining
- USD 63 million Series C in August 2026 to expand as a context layer for agents
Keep in mind: The approach requires software on employees’ workstations, so works councils and data protection officers should be involved early.
iGrafx Process360 Live
Vendor: iGrafx
Best for: Modeling, simulation and repository
In Process360 Live, iGrafx combines process mining, process design, simulation and a governed process repository. According to the vendor, iGrafx is a Leader in The Forrester Wave: Process Intelligence Software, Q3 2025; in January 2026 the company announced a collaboration with NTT DATA INTRAMART toward autonomous, agent-supported operations.
- Mining, design and simulation in one environment
- Governed process repository as a shared knowledge base for teams
- Digital twin capabilities for what-if scenarios
Keep in mind: For executing actions, iGrafx relies on partner technology – so the execution layer has to be planned separately.
What Will Matter in 2027
From mining to intelligence
In 2026, Gartner renamed the market process intelligence and now evaluates more than discovery and conformance. 2027 will show which platforms genuinely connect context, analysis and execution.
Process context for AI agents
Agents need to know how processes actually run in order to act sensibly. Knowledge graphs and open interfaces such as the Model Context Protocol are becoming standard equipment.
Traceability instead of a black box
The more decisions agents prepare, the more important verifiable cause-and-effect chains and human approvals become. Platforms that can evidence their recommendations gain trust.
Frequently Asked Questions
What is the difference between process intelligence and process mining?
Process mining reconstructs process flows from the event data of IT systems. Process intelligence goes further: it connects these flows with business context, enterprise knowledge and AI, explains causes and supports actions through to measuring their impact. Process mining is therefore one building block of process intelligence.
Which process intelligence platforms did Gartner rate as Leaders?
In the Magic Quadrant for Process Intelligence Platforms of May 2026, which evaluates 13 vendors, Celonis, SAP Signavio, ARIS and Pegasystems are positioned as Leaders according to the vendors. The report is the renamed successor of the earlier Magic Quadrant for Process Mining Platforms. In 2026, Gartner recognized Noreja in “Coolest Vendor Innovations in Process Intelligence”.
Do AI agents need a process intelligence platform?
Agents act only as well as they know the process they work in. A process intelligence platform provides that context: how flows actually run, where deviations arise and which rules apply. At Noreja, this context lives in an Event Knowledge Graph that the AI assistant Minerva and specialized agents use directly.
Which process intelligence platform fits which organization?
SAP-centric companies find the tightest integration in SAP Signavio, service-heavy organizations in ServiceNow, and automation programs in UiPath, Pega or Appian. Anyone who wants to understand causes across systems, independent of one ecosystem, and use the process context for their own AI is well served by a graph-based, causal platform such as Noreja.
How much does a process intelligence platform cost?
Many vendors quote prices only on request. Costs typically depend on data volume, number of users, modules and AI usage. Noreja publishes its packages transparently on its pricing page.
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