Nussknacker

 

act on data in real-time

a tool that makes data actionable for the domain expert

 

 

the muscle of real-time data systems

with Nussknacker, users build and deploy event-driven business automations. They have access to all the data they need and can quickly deploy real-time action solutions

integrates with Kafka-compatible platforms

existing Kafka deployments gain the ability to execute business logic in real time

user-friendly Flink processing

a deployed decision scenario becomes a Flink job in data streaming use cases

multipurpose

Nussknacker adapts to a wide range of applications, from common to cutting-edge

 

real-time data

 

event streams can be enriched with information from multiple sources: private and public APIs, databases, and Machine Learning models

 

 

low-code interface

 

the data is made readily available to the user via the drag-and-drop, one-click deployment interface that allows them to iterate and experiment

 

 

real-time apps

 

raw events become real-time business applications - without spending developer time

users innovate in response to changing business conditions creating event-driven solutions in faster cycles

product

ease of use

  • flow diagrams for decision algorithms
  • powerful expression language
  • autocompletion and validation
  • testing and monitoring tools
  • REST (OpenAPI) and data base (JDBC) enrichments
  • ML models inferring enrichments
  • one-click deployment
  • version history

deployment flexibility

  • running on Flink or K8s-based lightweight engine
  • Kafka® and HTTP interfaces
  • integrates with Kafka-compatible platforms like Confluent® Cloud, Azure Event Hubs® and Aiven® for Apache Kafka®
  • streaming and request-response modes
  • customisable and extensible
  • open source with enterprise extensions
  • on premises and cloud

building block

Real-time marketing

Communications with customers in real-time, providing event-driven offers and actions
Read a customer story

Fraud management

Mitigating fraud by running detection algorithms on network or device signals
Read a customer story

 

Next Best Action

Assisting the Point Of Sale, displaying suggestions about what to offer and how to proceed with a customer

 

Customer data processing

Decisioning on dynamic customer data in
- dynamic pricing
- order status management
- instant credit scoring

Internet of Things

Automating actionable data in
- predictive maintenance
- inventory management
- smart devices
See demo

ML models deployment

Infer Machine Learning models from within complex decision algorithms
Read a blog post

performance

as a showcase, we present here two deployments that demonstrate the power of the solution in the case of the telecom company PLAY (part of the Iliad Group)

cloud pricing

services

It's open-source, but we can help you get the most out of Nussknacker

blog

next steps