Process Intelligence Solutions provides PM4Py, an open‑source Python library, and PMTk, a no‑code graphical toolkit for process mining. The tools import event logs (XES, CSV, BPMN, SQL), automatically discover process models, perform conformance checking, and analyze performance, variant and object‑centric data, with support for streaming and AI‑driven predictions. They are available on‑premise, self‑hosted SaaS or managed cloud, with optional consultancy.
Funding
Funding not disclosed
Founders
Product
Problem
Organizations often struggle to extract actionable insights from event logs because traditional process analysis tools are either heavyweight, require extensive coding, or lack integrated visualization and conformance capabilities. This hampers the identification of bottlenecks, variant behaviors, and compliance gaps, leading to inefficient operations and missed optimization opportunities.
Solution
Process Intelligence Solutions (P.I.S.) addresses these challenges with two complementary offerings: PM4Py, an open‑source Python library that implements a comprehensive suite of process‑mining algorithms, and PMTk, a user‑friendly toolkit that packages the same analytics in an intuitive graphical interface. Together they enable users to import event data from common formats (XES, CSV, BPMN, SQL databases), automatically discover process models, perform conformance checking, analyze performance metrics, and explore variant and organizational perspectives. Advanced features such as object‑centric mining, streaming process mining, and AI‑driven predictive analytics extend the analysis to complex, real‑time environments. The solutions are available under flexible licensing (on‑premise standalone, self‑hosted SaaS, or fully managed cloud) and can be complemented by consultancy services for end‑to‑end project execution and custom integration.
Target Audience
Primary users are process analysts, data scientists, and business‑process managers in enterprises seeking to optimize operational workflows, as well as academic researchers and students requiring a robust, extensible process‑mining platform.
Features
- Process discovery engines (Alpha, Heuristic, Inductive, BPMN, object‑centric) that generate Petri nets, process trees, and BPMN 2.0 models directly from event logs.
- Conformance checking suite (token‑based replay, alignments, footprints, log skeletons) to quantify deviations between recorded executions and reference models.
- Performance and variant analysis tools (throughput, bottleneck detection, dotted‑chart visualizations, calendar view) with interactive dashboards and customizable widgets.
- No‑code data filtering with SQL support, filter chains, and trace‑level selectors for rapid data preparation without scripting.
- Streaming process‑mining modules for real‑time DFG discovery, conformance, and temporal profile computation on event streams.
- Object‑centric event log handling (OCEL import/export, OC‑DFG, OC‑PN, object‑graph analysis) for multi‑entity processes.
- Integration capabilities: Python API, REST endpoints, and export to standard formats (XES, BPMN, CSV) for downstream analytics or EHR/ERP systems.
- Deployment options: native desktop app (Windows/macOS/Linux), containerized self‑hosted web app, or cloud SaaS with collaborative workspaces and role‑based access control.