Intuitive Process Intelligence
Extracted data from your operational systems, typically ERP, and for most processes that means a handful of tables. Our Data Preparation Tool turns them into a clean event log, so you do not have to arrive with a finished one. If you already have an event log, we can work with that too.
No. Unlike our well-known integrations for Microsoft or Qlik, process.science Intelligence is designed as a completely standalone platform. All you need are your extracted ERP data.
Intelligence ships with default process norms that cover the deviations every process has: rework loops, skipped steps, broken sequences, unusual waiting times. Monitoring therefore starts with your first data set. In Setup you can sharpen those norms, or store a target process as a reference, whenever you want to be more specific about your own business.
You do not have to form a hypothesis and then filter your way towards it. Intelligence searches your data for the factors that drive a problem by itself, for example one supplier, one plant or one order type appearing disproportionately among the delayed cases, and ranks them by how strongly they are associated. It then shows you the evidence behind each one, so the finding can be checked rather than believed. The last step, deciding that a driver is the cause and acting on it, stays with the people who know the business.
Yes, because the chat does not estimate them. Your question is translated into a query against your process data, and the answer comes from the same calculations that produce the analysis views. Every finding you keep as an insight stores the tool, the time window, the filters, the selection, the affected population and the data set version, so anyone can check the number later.
No data science expertise is required. There are three roles: an Admin for projects and data sets, an Analyst who configures Setup and runs the analyses, and business users who read insights and ask questions in the chat. Most of the day-to-day use sits with people who know the process, not the database.
Your process data stays inside the environment agreed with you and is never used to train public models. The language models we use are ring-fenced enterprise models. Process.Science operates GDPR-compliant and is ISO 27001 certified, and access rights control which processes and data each user can query.
The Data Preparation Tool builds and maintains the event logs, Intelligence analyses them, and the IoT Miner adds machine and sensor data where your process reaches the shop floor. They work together, and each one can be used on its own.
