Tooling & accelerators for platform teams.

Niche solutions for data, infrastructure and API management.

API & Data Monetization

Monetization’ solution. Transition seamlessly from mere data reservoirs to lucrative revenue streams, leveraging a systematic approach to discovery, productization, and user-friendly access. Ensure your consumers enjoy a streamlined subscription experience, backed by real-time, usage-based billing, encapsulating the essence of modern monetization strategies.

  • Data & API Discovery

    Embark on a journey of identifying high-value data sets and APIs, setting the stage for potent monetization strategies.
  • Seamless Productization

    Transform raw data assets into polished, market-ready products, optimizing them for varied consumer needs and maximizing revenue potential.
  • Self-Service Subscription Models

    Empower consumers with intuitive self-service subscription portals, ensuring frictionless access to data products and API services.
  • Real-Time, Usage-Based Billing

    Implement agile and transparent billing mechanisms that resonate with modern consumption patterns, capitalizing on real-time usage metrics for optimal monetization.

Asynchronous Eventing for APIs

Bridge the gap between APIs and event-driven architectures with our ‘Event Bridge for APIs’ solution. Seamlessly map API transactions to events, harness the dynamism of command & event processing, and ensure flexible consumption via Cloud Events. Dive into the future of system integration, complemented by robust aggregate projections.

  • API Transaction to Event Mapping

    Flawlessly transform real-time API transactions into decipherable events, ensuring synchronization and coherence across systems.
  • Command & Event Processing

    Orchestrate streamlined command execution and event processing, promoting data accuracy and enhanced system interactivity.
  • Cloud Events Consumption

    Embrace the adaptability of Cloud Events for easy event consumption, fostering integration agility across diverse platforms.
  • Aggregate Projections

    Benefit from comprehensive aggregate projections, offering a consolidated view of events, driving analytical prowess and informed decision-making.

Platform Operations & Observability Stack for Apache Kafka & Confluent

Dive deep into the intricacies of efficiently managing Apache Kafka with our robust ‘Operations & Observability Stack’. Harness the power of streamlined cluster operations, blended with the agility of GitOps for Kafka resources. Elevate your observability standards, ensuring system transparency, while also fortifying your setups with focused security operations.

  • Cluster Operations

    Master the art of smooth Kafka cluster management, ensuring stability, performance, and resilience in real-time data flows.
  • Self-Service GitOps for Kafka Resources

    Incorporate the principles of GitOps, allowing teams to self-manage Kafka resources through version-controlled declarative configurations.
  • Advanced Observability

    Gain unparalleled insights into Kafka operations with advanced metrics, logs, and traces, driving proactive issue resolution.
  • Focused SecOps

    Uphold the security posture of your Kafka deployments, integrating best-practice security operations that ensure data integrity and confidentiality.

Data Fabric for Streaming Data Movement

Dive into a new realm of data integration with our ‘Data Integration Fabric for Streaming’. Tailored for the streaming era, this solution is geared towards empowering real-time data movement, ensuring impeccable integration, and fostering agile responsiveness in the face of ever-evolving data streams

  • Unified Data Movement

    Seamlessly transport data across various sources and sinks, capitalizing on high-throughput and low-latency streaming mechanisms.
  • Stream-Layer Integration

    Integrate multiple streams, irrespective of the origin, ensuring data consistency and alignment in real-time scenarios.
  • Dynamic Data Topology

    Leverage a malleable data topology framework, adapting effortlessly to changing data requirements and architectural nuances.
  • Scalable Processing Engines

    Optimize data flow and processing with scalable engines, ensuring smooth handling of massive data streams without sacrificing performance.