Crosser develops a low-code streaming analytics and integration platform that enables real-time data processing and automation across edge, fog, and cloud environments. The platform addresses the challenge of fragmented data management by providing a unified namespace and intelligent integration capabilities, allowing businesses to efficiently connect, transform, and act on data from diverse sources.
Funding
$8.7M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
MVNDFounders
Product
Problem
Many organizations struggle with fragmented data environments, making it difficult to process and integrate data in real-time across edge, fog, and cloud infrastructures. Traditional ETL and iPaaS solutions often lack the necessary capabilities for low-latency processing and unified data management, leading to inefficiencies and delayed insights.
Solution
Crosser provides a low-code, unified platform for streaming analytics and integration, enabling real-time data processing and automation across hybrid environments. The platform offers a unified namespace (UNS) to connect, transform, and act on data from diverse sources, including IoT devices, machines, and cloud applications. By combining stream analytics, ETL/ELT, and iPaaS functionalities, Crosser empowers users to build intelligent integration pipelines with minimal effort, facilitating event-driven architectures and real-time experiences.
Target Audience
The primary target audience includes data engineers, IT professionals, and business users in industries such as manufacturing, IoT, and logistics who need to integrate and process data in real-time across hybrid environments.
Features
- Low-code Flow Studio for rapid development of integration and automation pipelines
- Unified Namespace (UNS) for a single version of the truth across data sources
- Real-time processing capabilities for data-driven automations and actionable insights
- Connector library with 800+ pre-built connectors for diverse data sources and destinations
- Support for Change Data Capture (CDC) to keep data synchronized across systems
- Hybrid deployment options with centralized control for cloud, on-premise, and edge environments
- Crosser FlowWatch for data observability, monitoring, and validation of data flows
- Built-in modules for data transformation, stream analytics, and advanced logic