Skip to content
ORELSIS
TR
Data Management Platform

OREL DM

Unify your data and turn it into value with AI.

OREL DM is data management software that unifies scattered data sources on one platform with integrated AI and orchestration capabilities.

Request a demoProduct tour
ORELSISDM

Model studio · energy forecast v7

Live·Specific energy · actual vs. predicted
StatusIn production38 features · 12 d ago
Actual · kWh/t
Click to pin a point
2,3502,4002,4502,500Sep 22Sep 27Oct 2Oct 7Oct 12Oct 17Target 2,400
Feature importance — %
Current density · 41% of totalTotal 83 %
What is it?

What is OREL DM?

OREL DM is data management software that unifies scattered data sources on one platform with integrated AI and orchestration capabilities. It collects, cleans and governs data from production, quality, maintenance and business systems so it can be trusted. By letting you design and run data pipelines and AI models in the same environment, it takes forecasting, anomaly detection and decision-support applications into production.

Who is it for?

For data and analytics teams, digital transformation leaders, and companies that want to take AI projects from pilot to everyday use.

What you get
  1. You bring field and business data into a single, trusted source.
  2. You know instantly when and why a data pipeline stops.
  3. You train and deploy AI models reproducibly.
  4. You prove where each piece of data came from with lineage.
Data unification

Six sources, three different records, one true version

Events from ERP, machine, CRM, file, sensor and API sources flow into the common data model. The same customer, material or machine arrives with different IDs and spellings; it is matched and becomes a single golden record in which you can see which source every field came from. Forecasting, anomaly and classification models run on this unified data.

  • ERP
  • MES / PLC
  • CRM
  • Files
  • IoT sensors
  • REST API
Common data modelCustomer
ERPSample Machinery Inc.
CRMSAMPLE MACHINERY INC
CSVSample Machinery Co.
MUS-00018496%
Forecast−5.1%
Anomaly
Class
Normal 86%
Data pipeline · Live
Illustrative simulation
Sources
6
Events / s
9.3
Models
3
  1. 1

    Ready-made connectors

    Database, OPC UA, MQTT, REST and CSV/Excel sources are brought onto one pipeline; batch imports and live streams are monitored in one place.

  2. 2

    Matching and golden record

    The same entity across systems is merged under one identity with a match confidence; every report uses the same definition.

  3. 3

    Field-level lineage

    Every field in the golden record shows which source it came from; models produce forecasts, anomaly flags and classifications on this trusted data.

Features

What you can do with OREL DM

  • 01

    Data integration

    Sets up real-time and batch data flows from ERP, MES, SCADA, IoT devices and databases.

  • 02

    Orchestration

    Manages data pipelines and model workflows with dependencies, scheduling and retry rules, and monitors failures.

  • 03

    Integrated AI

    Trains, versions and serves models inside the platform, and connects forecasting and anomaly detection to business processes.

  • 04

    Data quality and governance

    Keeps data trustworthy with a data catalogue, lineage tracking, quality rules and role-based access.

  • 05

    Time-series and sensor data

    Stores high-frequency process and sensor data efficiently, with pre-processing on edge devices.

  • 06

    Analytics and dashboards

    Lets business units build their own dashboards and reports on trusted data.

Product tour

A step-by-step product tour

Screens are illustrative; your installation is configured around your processes.

ORELSISDM

Data sources

8 connections · last 15 min
LiveExport as CSV
SCADA-ELKOPC UA1,840120 msConnectedElectrolysis SCADA · 1,420 tags · 500 ms subscription.
PLC-DOL-AModbus TCP42080 msConnected
IoT-GW-02MQTT2,96045 msConnectedVibration and temperature sensors · QoS 1 · TLS.
HIST-01ODBC260210 msConnected
EMS-METERM-Bus96300 msConnected
SAP-PRDOData121.4 sSlowBatch query 1.4 s (threshold 1 s) · 3 timeouts in the last 15 min.
LIMSREST3640 msConnected
WMSREST4380 msConnected
8 of 8 records7Connected1Slow1–8 / 8
Modules

Modular by design

Start with the modules you need and expand as you grow.

  1. 01Data connectors
  2. 02Pipeline orchestration
  3. 03Data catalogue and lineage
  4. 04Data quality rules
  5. 05Time-series store
  6. 06Model training and management (MLOps)
  7. 07Model serving
  8. 08Edge data collection
  9. 09Dashboards
  10. 10Access and permission management
Integrations

Talks to your existing systems

Integrates through standard protocols and open APIs.

Kafka
PostgreSQL
OPC UA
MQTT
REST API
OREL DM
SAP
ERP
Kubernetes
Python
Excel
All integrations
Getting started

From first call to go-live with OREL DM

Every rollout follows the same four steps; the timeline and price are confirmed in the proposal, based on your scope.

  1. 01

    Discovery call

    We learn about your processes, existing systems and priorities, and demonstrate the product using your own scenario.

  2. 02

    Scope and proposal

    We agree the modules, integrations and timeline together, then send a written scope and proposal.

  3. 03

    Installation and data migration

    We install on your servers or in the cloud, migrate your master data and test the integrations.

  4. 04

    Training and go-live

    We train users by role, run a controlled cut-over and stay with you on site through the initial period.

Who we need from your team
  • A project owner who can make decisions
  • A lead who works with the process every day
  • An IT contact for server and network access
What the price depends on
  • The modules you choose
  • Number of users and sites
  • Deployment: on-premise, cloud or hybrid
  • Scope of integration and data migration

After the discovery call we confirm the scope and send a written proposal.

Request a demoLicensing and deployment options
FAQ

Frequently asked questions

OREL DM can work alongside your existing data warehouse or databases, or serve as the central data layer when needed. Its key difference is combining integration, orchestration, governance and AI on one platform.

Yes. Models developed in Python can be brought into the platform, versioned and served. Ready-made forecasting and anomaly detection templates can also be used as a starting point.

OREL DM can be deployed on-premise, in the cloud or as a hybrid. With an on-premise deployment, data and models stay entirely on your infrastructure; in a hybrid model, you decide which data is processed where.

OREL DM unifies data from OREL MRP, QMS, IMS and other products in a shared layer. This lets you, for example, use maintenance, quality and production data in the same model for cross-process analysis.
Related products

Better together

View all
Production & Planning

OREL MRP

Plan production, track the shop floor, improve continuously.

Quality Management System

OREL QMS

Automate your quality processes and regulatory compliance.

Maintenance Management System

OREL IMS

Plan maintenance and see failures before they happen.

Let's digitalise your operations together.

In a 30-minute call, we'll listen to your needs and show you the right OREL products live.

Request a demoContact us