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Today, Confluent is excited to announce the 10 global semifinalists for this year’s Data Streaming Startup Challenge! The Data Streaming Startup Challenge, first announced at Current 2023, is a global competition that aims to recognize and reward early-stage startups that are building innovative real-time applications with Confluent Cloud.
Nearly 100 young startups (less than five years old and with less than $10 million in venture funding) from 22 countries took part in this year’s global contest. This year’s applicants have successfully applied data streaming to a wide variety of industries and use cases—everything from online gaming and mental health support, to blockchain applications and artificial intelligence.
Over the years, startups have played a crucial role in adopting and shaping the future of open source software. In the 1990s, widespread startup adoption of Linux helped popularize the first open source operating system. During the transition to cloud computing early-stage startups have consistently been at the forefront of technology adoption and innovation, such as when startups helped revolutionize containerization with their early adoption of Docker and Kubernetes or when they were the first to embrace cloud databases like MySQL and MongoDB. These forward-leaning startups not only developed new use cases for the technology, they actually helped drive its broadscale adoption across industries and across borders. The same is happening today with data streaming and Confluent is turbocharging the process with the $1M Data Streaming Startup Challenge!
Each of the 10 global semifinalists will receive $5,000 in Confluent Cloud credits and two tickets to Kafka Summit London. Most importantly, they are still in the race to be crowned this year’s Data Streaming Startup Champion, which includes a game-changing $500,000 investment from Confluent and the opportunity to pitch the investment teams at Benchmark Capital, Sequoia Capital, and Index Ventures! Each of these finalists exemplifies the innovative spirit and technical imagination that is sure to propel data streaming to the forefront of 21st century critical use technologies.
The entire Confluent community, along with our venture capital partners, wishes the 10 semifinalists a hearty congratulations and the best of luck in being named one of the three finalists that will be flown to London to present on the main stage at Kafka Summit London on March 19!
Aklivity (Palo Alto, CA): Aklivity builds API infrastructure for connecting apps and services to streaming data. Aklivity natively supports the Kafka wire protocol and uses novel protocol mediation techniques to establish stateless API entry points into Confluent Cloud.
Allium (New York, NY): Allium provides high fidelity and low latency real-time and enriched data for blockchain. Allium uses Confluent Cloud to process high-volume data across multiple chains and enriched entities during each phase of extraction, transformation, and loading process.
Atomic Tessellator (Auckland, New Zealand): Atomic Tessellator is an AI-powered, real-time computational chemistry platform. Atomic Tessellator uses Confluent to create nonlinear data pipelines that put "molecules in motion" in order to create artificial computational chemistry experiments.
Bleaum (Miami, FL): Bleaum is a comprehensive e-commerce platform designed to meet the unique needs of the cannabis industry. Leveraging Confluent for real-time analytics and inventory management, and Kafka for compliance and regulatory adaptability, Bleaum also offers an advanced point of sale system. This integration of cutting-edge technologies ensures a seamless and compliant experience, providing a holistic solution for the cannabis market.
Busie (Kingston, NY): Busie is the operating system for group transportation. Confluent allows Busie to perform asynchronous inter-service communication, reducing the overall complexity of Busie's architecture as well as the operational burden of adding or removing business capabilities according to business requirements.
DRVR (Bangkok, Thailand): DRVR uses the smartphone as a sensor to detect road accidents and improve safety. At the heart of DRVR's service is an event driven engine which allows them to identify poor driving behavior. They use the Kafka events steams to identify driving behavior events that may cause accidents and waste fuel.
Ecofye (London, UK): Ecofye offers an automated, real-time emissions monitoring platform. Confluent is being used by Ecofye as the primary source of truth for all of the company’s data streaming requirements.
Golden Whale Productions (Vienna, Austria): Golden Whale develops machine learning-enabled gaming infrastructure. Golden Whale uses ksqlDB to create running aggregates and enrich the events with contextual data, turning them into a schema used by their models. The aggregate stream is consumed by the prediction service, which then pushes back these predictions to the end customer using a data stream.
OpenMeter (San Francisco, CA): OpenMeter is a scalable metering and monetization platform that turns AI and API usage into revenue. OpenMeter uses Confluent Cloud to collect AI and infrastructure usage events and uses a stream processing pipeline to aggregate these events into usage.
Revend (Antwerp, Belgium): Revend helps direct-to-consumer e-commerce brands monitor activity and catch glitches on their shops in real time. Revend delivers the power of "right now" to e-commerce operators by using Confluent data streaming to ingest and process clickstreams in real time.
Soulside (Mountain View, CA): Soulside is using AI and real-time data to power mental health for high risk groups. As patients talk about their life journeys, the transcripts are streamed using Confluent to Soulside's backend servers, which processes them in real time, and assists the facilitators in real time via cues/prompts to deliver more personalized support.
TwinLabs AI (London, UK): TwinLabs is a real-time SaaS digital twin platform. TwinLabs uses Confluent to ingest, integrate, and process diverse data sources in real time and in a scalable manner.
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