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

 

see demo

 

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

use cases

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

webinar

June 11th: "Real-time data processing for the people. How far is it to nirvana?"

Imagine domain experts building powerful apps (fraud detection, sensor analysis, etc) without needing tons of code. What are required features that bring us closer to this goal?

blog

next steps