Nussknacker has been deployed in various companies and domains
As a showcase, we present here three deployments that demonstrate the power of the solution in the case of the telecom company PLAY (part of the Iliad Group)
Nussknacker has been deployed in various companies and domains
As a showcase, we present here three deployments that demonstrate the power of the solution in the case of the telecom company PLAY (part of the Iliad Group)
→ Transformed batch-based marketing campaigns into real-time interactions
→ Eliminated multiple-day delays in campaign execution
→ Addressed the challenge of managing complex business rules and campaign logic
→ Eliminated the delay in fraud detection from batch processing
→ Addressed complex SIM card fraud schemes that were hard to detect
→ Solved the challenge of managing complex detection rules
→ Seamless integration of complex ML models
→ Reduced time-to-market for new features
→ Faster implementation of business rule changes
→ Domain experts can directly manage workflows
How to simplify the integration of ML models into business applications, automate many of the technical complexities, and support advanced techniques like A/B testing and ensemble models. A fraud detection example.
Business scenarios can become increasingly complex, causing many problems for users and administrators. Read how we tackle the problem in the Request Response processing example.
Nussknacker simplifies the integration of machine learning models into streaming data processes. Software teams can now build intelligent recommendation systems using Nussknacker, Snowplow, and MLflow.
Nussknacker effortlessly integrates with Apache Kafka, including Kafka's Schema Registry. We illustrate these concepts through an Internet of Things example, showcasing the real-world application of Kafka integration with Nussknacker.
Explore real-world case studies from industries like telecom, finance, and e-commerce. See how teams use Nussknacker to build real-time fraud detection, credit scoring, IoT automation, and more-without heavy coding. Get inspired and start your journey today.
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By supporting the widely-used MQTT protocol, Nussknacker makes it easier to connect to and process data from various IoT sensors and devices without needing custom connectors.
Fraudsters act instantly, and fraud detection systems must keep up. Yet, many businesses still rely on slow, outdated batch processing. This post explores the challenges of real-time fraud detection and how Nussknacker’s low-code platform enables fast, efficient transaction monitoring.
Using Nussknacker with MLflow, enabled data scientists to deploy ML models directly while letting business analysts manage credit rules. This resulted in faster updates, reduced developer dependency, and more efficient credit risk assessment for their 13 million customers.