HaROS · Platform

Always current, a platform that stays up at peak: HaROS Platform

HaROS is continuously updated; version upgrades never become your project. Stock, orders, customers and products run in real time on a single data layer.

In brief

HaROS Platform is the layer the WMS · OMS · PIM · TMS modules run on. It stays current continuously. It is set up on top of your existing ERP and goes live module by module.

Core principles

Four principles that keep the platform standing

HaROS Platform is not made of features added later. It is the result of four decisions taken since day one of the architecture.

01 — Architecture

In the cloud, container-based

A microservice architecture that runs in containers on cloud infrastructure. Services scale independently; the load on one module does not affect another.

02 — Continuous updates

Always current

The platform is continuously updated; version upgrades never become your project. You avoid the risk and downtime of major version migrations.

03 — Data

Data Fabric: one data layer

Stock, orders, customers and products sit in a single data layer. Modules work in real time on the same data instead of separate copies.

04 — Flow

Event-based processing

Sudden load increases are collected in a queue and processed in order. Instant reporting shows what is happening while operations continue.

HaROS Data Fabric

All teams work on the same data

In a fragmented setup, stock sits in one system, orders in another, customers and products elsewhere. Data Fabric brings these four areas together in a single layer in real time.

STOCK

Stock

One stock figure across warehouse, store and channels.

ORDER

Orders

Store, online, marketplace and B2B orders in a single pool.

CUSTOMER

Customers

Consistent customer and address data, independent of channel.

PRODUCT

Products

One catalog; product data in sync across all channels.

HaROS DATA FABRIC

Four data domains, real-time and consistent. Modules do not keep separate copies; they read and write the same data.

Performance and resilience

A predictable operation at peak too

HaROS stays predictable under load spikes through continuous monitoring, service isolation and a restricted operating mode.

Fast

API response time

API requests are answered quickly at peak too.

Read replica

Reporting does not slow live operations

Heavy reports run on a separate read replica; they do not affect live operational performance.

Restricted mode

Stays up on partial failure

If a component is under strain, the platform does not go down entirely; it keeps running in a restricted mode. Core operations continue.

Grafana

Continuous monitoring

Metrics and traces are continuously monitored with Grafana and Elastic APM; alerts are raised when thresholds are exceeded.

Event-based

Queue-based processing

Sudden load increases are collected in the queue; the system processes the work in order instead of clogging.

Updates

Updates without stopping operations

Updates are applied without stopping operations.

120,000+
orders/day
150,000+
product lines
40,000/hr
orders at peak
Modular structure

Set up on top of your ERP, without replacing it

Your existing ERP (SAP, Oracle, Logo, Nebim, Mikro and others) stays in place; HaROS is set up on top. Modules go live step by step, not all at once.

On top of ERP

On top of your existing ERP

Your ERP stays in place; HaROS modules connect through 100+ ready-made integrations.

Module by module

Go live step by step

First the core module (mostly HaROS WMS or OMS), then the others go live. Your operation continues.

Planned in discovery

A shared timeline

Rather than promising a fixed duration, a realistic plan is built from the scope in the discovery phase — without the risk of switching everything at once.

Frequently asked questions

How does HaROS stay current?

The platform is continuously updated; new features and improvements arrive with these updates. You are never left on an old version, and version upgrades never become your project.

Do updates stop operations?

No. Updates are applied in small steps while operations continue. Services are updated independently of each other; on a partial failure the platform keeps running in a restricted mode.

How is my data held?

Data is held in a single operational layer in HaROS Data Fabric.

Does heavy reporting slow down live operations?

No. Reports run on a separate read replica and do not slow live operations. While instant reporting runs, API responses stay fast.

See the platform with your own operation

In a short discovery call, let's talk about how HaROS takes shape around your operation.

Request a demo