Our mission has always been simple: to build beautiful software that people love to use. We aim to take the boring parts of the real-time data journey, in order to enable engineers to focus on delivering new digital experiences.
So there’s nothing better than meeting customers enjoying using your software while immediately delivering business value.
I am feeling lucky to work with the most exciting companies in their fields including world-class organisations and innovative technology businesses. From startups such as Nuvo that provide wearable pregnancy monitoring devices to unicorn tech companies such as Babylon Health, teams of all sizes are gaining value from DataOps using Lenses.
The common theme with all of them: Building streaming data platforms is tough. Getting the platform and data intensive flows in production is even tougher. Yet that’s exactly what we help our customers with. Simplifying this journey is what we call DataOps. Here are a few examples:
One of the world’s largest mobile and social gaming companies they develop games such as Tropicats and Pirate Kings. Lenses makes over 600 developers, QA, data and operations analysts more productive by giving them direct access to see inside their Apache Kafka streams using SQL. They estimate this saves an average person 30 mins per day. Read the full story
A fintech that develops AI-based risk models for their finance customers. The more they can empower their data science team to directly access streaming data, the more value they can deliver to the market. This is an example of where Lenses reduces the need to have a large team to manage the data infrastructure and build flows. Read the story
A SaaS product for reporting and AI-driven analytics on the position of seabourne energy freight (such as crude oil) to energy traders. Not only is Lenses critical for monitoring the performance of their Kafka platform and flows but it also provides the framework to build and deploy new streaming flows. With Lenses, configuration is all they need to work with rather than code. It also delivers a feedback loop whilst building and deploying - to detect config errors, validate flow is deployed in a topology view and to inspect/validate the data in the stream. They estimate they can deploy streaming flows to production 95% faster with Lenses against traditional methods. Read the story
Discover the different usecases for Lenses here