What is Condense

Condense is an AI-native, real-time data streaming platform for building, deploying, and operating real-time applications.

Built on Apache Kafka, Condense brings together application development, real-time data streaming, stream processing, data integration, deployment, and operations in a unified platform.

Condense enables applications to consume streaming data, apply real-time business logic, process and transform events, and deliver outputs to downstream systems. The platform abstracts the complexity of operating Kafka and the supporting infrastructure, providing a consistent environment from development through production.

Why Condense?

Building and operating real-time applications requires multiple technologies and operational components, including Kafka, connectors, stream processing, infrastructure, deployment, and observability. Managing these components independently increases engineering and operational complexity.

Condense provides a unified platform for the complete real-time application lifecycle.

Build Real-Time Applications

Develop applications that consume streaming events, process data in real time, and respond to events as they occur.

Develop on Streaming Data

Implement application and business logic directly around real-time events, enabling applications to filter, transform, enrich, aggregate, and route streaming data.

Connect Data and Applications

Integrate applications with data sources and destinations through prebuilt connectors, reducing the effort required to build and maintain individual integrations.

Deploy and Run Applications

Move applications from development to production through a unified deployment environment without independently managing the underlying streaming infrastructure.

Scale with Data

Scale applications and streaming workloads as data volumes and processing requirements increase.

Operate from a Unified Platform

Manage applications, streaming workloads, Kafka infrastructure, connectors, and operational workflows from a single platform.

Accelerate Operations with AI

Use Vapr AI to assist with development, troubleshooting, monitoring, and operational workflows across the streaming environment.

Key Features

Real-Time Application Development

Build event-driven applications that consume, process, and respond to streaming data. Condense provides the development and runtime capabilities required to implement application logic around real-time events.

Application Logic

Define application logic for processing incoming events and generating real-time outputs. Applications can filter, transform, enrich, aggregate, and route data based on defined business requirements.

Real-Time Data Streaming

Use Apache Kafka as the underlying event streaming platform to reliably move data between applications, services, and systems in real time.

Stream Processing

Process streaming data as events occur through transformations, filtering, enrichment, aggregation, and routing.

Data Integration

Connect applications and streaming workloads to data sources and destinations through prebuilt connectors.

Application Deployment

Develop, deploy, and operate real-time applications and their associated streaming workloads through a unified platform.

Managed Kafka

Provision, configure, scale, and operate Kafka through Condense without independently managing the underlying Kafka infrastructure.

Observability

Monitor applications, streaming workloads, Kafka, connectors, and infrastructure through integrated observability and operational monitoring.

Autonomous Scaling

Scale streaming infrastructure and workloads based on application and data requirements.

AI-Assisted Operations

Vapr AI assists with application development, troubleshooting, monitoring, and operational workflows across the Condense platform.

Bring Your Own Cloud

Deploy Condense within the customer’s AWS, Azure, or GCP environment while retaining control over the underlying cloud infrastructure and data.

Security and Governance

Apply authentication, authorization, schema management, access controls, and governance policies across applications and streaming workloads.

Let’s understand what Condense is solving

The adoption of real-time data has solved one part of the problem: organizations can now capture and move continuously generated events from vehicles, devices, applications, databases, and enterprise systems. However, turning those events into production-ready real-time applications still requires multiple independent technologies and operational layers. Teams typically have to integrate streaming infrastructure, connectors, stream-processing frameworks, application runtimes, deployment infrastructure, scaling mechanisms, observability, security, and domain-specific processing. Each layer introduces its own configuration, development model, operational requirements, and expertise, while the integration between them adds further complexity.

The problem becomes more significant as real-time applications move beyond simply consuming events and begin performing continuous processing and operational actions. A streaming platform can transport an event, but the application still needs to determine how that event should be transformed, enriched, correlated, interpreted, and used. These requirements also vary by domain. Vehicle telemetry, for example, may need to be converted into trips, geofences, vehicle-health indicators, or fleet events, while industrial, logistics, energy, or other operational systems require their own domain-specific processing.

As a result, organizations often have to solve two problems independently: building the technology foundation required to run real-time applications and building the domain capabilities required to derive value from real-time data. The resulting architecture is fragmented across infrastructure, applications, and specialized domain systems, increasing development effort and operational complexity.

Condense addresses this gap by bringing the capabilities required to connect data, manage streaming, process events, run applications, and operate them in production into a common platform, while providing an ecosystem through which specialized domain capabilities can operate on the same real-time foundation.