Hey Product Hunt Community, Enso co-founders, Wojciech and Sylwia here! @mwseibel thanks for hunting us! 😨 THE PROBLEM Data analysts still waste up to half of their time on repetitive manual work that can be automated [1]. To give one example, a company we're working with hires hundreds of business users who use Excel to define data quality rules. These get manually translated to SQL, then manually translated to Python. This is not only error-prone, it’s so slow that it takes them 90 days to introduce a single new rule. There’s 60 days’ worth of overhead in this process—it’s absolutely insane! [1] https://www.alteryx.com/e-book/i... 👋 OUR BACKGROUND Years ago I (Wojciech) led the in-house development of visual effects (VFX) tools at a motion picture studio. We made tools like cloud renderers and smoke simulation engines. The artists using these tools did not have any programming background, yet they were designing complex algorithms for forces between particles, light subsurface scattering, things like that. Earlier generations of these tools had hundreds of config options, buttons, etc., for masses of different use cases, but this approach got way too complex and people eventually realized that it falls short when you need to do anything that the vendor did not think of. Nowadays they use node-based software (like the Houdini FX) which lets users draw algorithms as a sequence of data processing steps (these steps are often referred to as “nodes”). Later, when I was working in other industries and encountered the same rats’ nests of complex GUIs for solving data processing problems, I realized that the data analytics/science space was in need of the same breakthrough that we had already gone through in the VFX space. Btw, if you are interested in how these VFX tools we did worked, here is an example of cloud sceneries built and rendered with my tools:

🧠 WHY ENSO IS UNLIKE ANYTHING YOU'VE USED SO FAR? Most workflow-builders / visual programming languages do not scale well because they don't let users express abstractions. Try to build a complex pipeline and you'll end with an unreadable spaghetti of connections—it's like coding a web app in assembler. Enso is different because we allow you to build abstractions to manage the complexity. As a result, you never have more than 10-20 nodes on the stage in Enso (nodes are hierarchical). You can create custom data types, custom components (functions), catch errors, etc. All this works because under the hood, Enso is a real programming language. However, naive implementations of such systems are super slow. Each component may be built of hundreds, sometimes thousands of lower-level ones. The real trick is making these hierarchical components run fast. For that, you need a dedicated compiler and a runtime system, and this is a hard technical space. Our system involves a dedicated polyglot JIT compiler based on GraalVM (https://www.graalvm.org). "Polyglot" means that you can add Java, JavaScript, R, and Python (soon also Ruby, Scala, Kotlin, Rust, and C) directly into Enso nodes without the need to write any wrappers and with a close-to-zero performance overhead. For details, see https://enso.org/language#compiler. In case this is an interesting topic for you, here is our podcast about how the compiler works under the hood:

❤️ ENSO IS 100% FREE AND OPEN SOURCE ❤️ Enso is 100% open source (https://github.com/enso-org/enso) and free to use (download it from https://enso.org). Our business model is based on selling domain-specific libraries, on-premise installations with enhanced user permission management, and coming soon, a hosted solution called Enso Cloud, which will be our only non-open-source codebase. Also, the Product Hunt launch is a perfect occasion to announce big things! ☀️ We are thrilled to announce that we have just started two amazing community projects in Enso: 1. The Enso Partnership Program. If you have an idea of what you want to build on top of Enso, apply, and we will provide you with a dedicated developer from our team, priority bug support, and amazing Enso SWAG (like t-shirts, stickers, hoodies). Apply here https://enso.org/partnership and join our community at https://discord.gg/enso! 2. The Enso School. Work together with our Data Analysts on real-world use cases and boost your skills. After the 8-week program, we will recommend the best of Enso School alumni to Y Combinator companies that are looking for Data Analysts! Apply here https://enso.org/school and join our community at https://discord.gg/enso!

🙏 We'd love to hear your feedback and answer your questions! 😀

Wojciech Daniło

Enso

Maker

4yr ago

Georg Untersalmberger

Probably the slickest data analysis tool I have seen for many years. Extremely exciting. Well done @wojciech_danilo and team!

@untersalmberger Thank you so much! The UX and the way you work is one of our main focus points here. Personally, I believe that only by introducing fundamental changes to how we are able to get "immediate connection to data" could become the basis for creating the next generation data analysis platform. It is, of course, very much connected to the Bret Victor's vision:

Oliver Rösner

I followed them since they were called Luna back in the days and recently tried out Enso. Super promising project and excited to see how it will develop while doing YC. Keep it up!

@retendo Thank you so much! We are doing our best to make Enso a super powerful tool in your toolbox ❤️

Enso

Analyze and visualize data by building data flow graphs

Analyze and visualize data by building data flow graphs

Enso

Analyze and visualize data by building data flow graphs

Analyze and visualize data by building data flow graphs

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