Crosser

What the product is

Crosser is a low-code platform for event processing, stream analytics, ETL and integration. Its site files it under "Enterprise iPaaS and Workflow Automation" and describes it as a way to "integrate streams, on-prem applications, SaaS apps, files and API's". It is built for IT, maintenance and operations teams, plus data teams, who need to move and act on data from machines, applications and files without a developer writing each pipeline. The company calls itself a "hybrid-first" streaming analytics and integration vendor for any cloud, on-premises site or edge location, and its CEO and co-founder is named on the site as Martin Thunman. The site does not say where the company is based.

What you build and how

You build in Crosser Flow Studio, a drag-and-drop design studio that the site says supports "+800 integrations and +100 modules" for transforming data and applying processing logic. A flow is a chain of modules on a canvas. The company says the modules share a consistent messaging model and user interface, and that third parties can supply modules under similar conditions. If a module is missing you can build your own with the code modules or the open SDK the site mentions.

What a flow can do is described in plain terms on the site. You connect IoT devices or other streaming and enterprise sources, then transform, filter, clean and enrich the data. You add logic through event processing, conditions, custom code or machine learning models, and you use actions to build workflows with triggers, alerts and notifications. The data sources the home page lists are IoT and machines, video and audio, transactions, logs and apps, plus batch data, files and APIs. It also lists change data capture, which reacts to new, updated or deleted data. Transformations can use standard modules or SQL, and a flow can send results to a destination in the cloud, on-premises or at the edge.

3 of the platform's named solution areas map to different jobs. Cloud Data Integration covers event-driven data lake and data warehouse integration. Enterprise iPaaS and Workflow Automation covers integrating streams, applications, files and APIs. Power Real-time Applications is about making applications event-driven. A fourth area, Industrial IoT Data Integration, sits under an Industry 4.0 heading. On Azure, the company says devices can connect to Crosser directly over MQTT or HTTP without using Azure IoT Hub, and that flows can write to Azure Storage services.

The runtime is separate from the editor. Crosser Node is "the lightweight and high performing runtime that you install as a Docker container or as a native Windows service". Crosser Control Center is described as a SaaS service for designing, deploying and monitoring your data pipelines. The site calls this a hybrid deployment with one control plane: use Flows-as-a-Service for SaaS and cloud work, and self-hosted nodes for on-premises data or your own cloud. Once a flow is deployed on a node it runs autonomously, without relying on connectivity to the cloud, and the Control Center is only a management and configuration service.

Operating many nodes is part of the design. Groups are created by attaching labels to nodes, so overlapping or hierarchical groups are possible, and an operation works on a group as easily as on one node. The Control Center keeps version control of flows, modules and node software, and upgrades and downgrades can be managed on any number of nodes. FlowCodeSync loads modules dynamically into the generic runtime when you deploy, so maintaining a deployed use case does not mean updating locally installed software or a container.

Testing happens before production. The site describes remote testing: you check the data as it passes through each module, view individual messages as they are processed, or plot sensor data in a time series graph viewer. You can test in a sandbox that is part of the cloud service, or connect the flow editor to a node you have deployed in the field and use real data. Once verified, the flow is deployed to production from the same interface. FlowWatch then covers monitoring, with flow monitoring and alerts, data freshness monitoring and data validation named on the home page.

AI appears in 2 ways: you can add your own ML or AI model inside a flow, and the site talks about running distributed ML and AI at the edge, close to the data source.

What the pages state

Pricing. The company's home page and articles state no prices. The home page links to a "Features and Pricing" page, which is where plan names and limits would be found. Both the home page and the Azure article invite visitors to "Sign up for a free account for testing your ideas", and the page then says to design and deploy your first flows and pipelines. It does not describe the limits of that account.

Scale and cost claims. The company says the platform has "+800 integrations" and "+100 modules". Its home page claims "90% savings compared to Kafka" on infrastructure cost, and talks about offloading cloud work to hybrid edge, on-premises and multi-cloud setups to balance processing cost and performance. Treat these as the vendor's own claims.

Speed claims. The Azure article quotes the CEO: "Our customers build real-time applications that we call FlowApps in hours, not months." The home page promises to "build and deploy new pipelines in minutes with minimum effort".

Typical uses. The Azure article lists raw data processing and data reduction for optimized cloud spending, condition monitoring of assets, operational KPI and OEE calculations, and advanced automation workflows. It says the usual setting is edge analytics and factory floor Industry 4.0 use cases, and it describes the platform as designed for industrial and enterprise IoT.

Positioning. The company describes its product as "a real-time analytics, automation and integration engine for streaming data designed to remove complexity". The Azure article contrasts it with stitching together separate cloud services, saying users get an all-in-one platform with a low-code interface.

Support and compliance. The home page and articles do not name support channels, security certifications or customer counts.

Who it suits and who it does not

Crosser suits IT, maintenance and operations teams, and data engineers, who need streaming or event-driven data pipelines across a mix of machines, on-premises systems and cloud services. The CEO's own framing is teams that have no developers trained in advanced IoT or streaming data applications and want existing IT, maintenance or OT staff to build them. The self-hosted node and the label-based fleet management also fit teams that need to roll one flow out to many sites and watch them from one place.

It is a narrower fit for someone who wants to ship a customer-facing app, a website or a simple form automation. The product's vocabulary is pipelines, nodes, modules and streams, and the examples on its pages come from industrial and enterprise data work. Installing a node means running Docker or a Windows service, so someone has to own that runtime even though the editor is visual. And because the home page and articles publish no prices, a small team has to go to the Features and Pricing page or the sales team to work out cost before committing.