Skip to main content

Dark emerges from stealth with unique ‘deployless’ software model

Dark has been keeping its startup in the dark for the last couple of years while it has built a unique kind of platform it calls “deployless” software development. If you build your application in Dark’s language inside of Dark’s editor, the reward is you can deploy it automatically on Dark’s infrastructure on Google Cloud Platform without worrying about all of the typical underlying deployment tasks.

The company emerged from stealth today and announced $3.5 million in seed funding, which it actually received back in 2017. The founders have spent the last couple of years building this rather complex platform.

Ellen Chisa, CEO and co-founder at the company, admits that the Dark approach requires learning to use her company’s toolset, but she says the trade-off is worth it because everything has been carefully designed to work in tandem.

“I think the biggest downside of Dark is definitely that you’re learning a new language, and using a different editor when you might be used to something else, but we think you get a lot more benefit out of having the three parts working together,” she told TechCrunch.

She added, “In Dark, you’re getting the benefit of your editor knowing how the language works. So you get really great autocomplete, and your infrastructure is set up for you as soon as you’ve written any code because we know exactly what is required.”

It’s certainly an intriguing proposition, but Chisa acknowledges that it will require evangelizing the methodology to programmers, who may be used to employing a particular set of tools to write their programs. She said the biggest selling point is that it removes so much of the complexity around deployment by bringing an integrated level of automation to the process.

She says there are three main benefits to Dark’s approach. In addition to providing automated infrastructure, which is itself a major plus, developers using Dark don’t have to worry about a deployment pipeline. “As soon as you write any piece of backend code in Dark, it is already hosted for you,” she explained. The last piece is that tracing is built right in as you code. “Because you’re using our infrastructure, you have traces available in your editor as soon as you’ve written any code,” she said.

Chisa’s co-founder and company CTO is Paul Biggar, who knows a thing or two about deployment, having helped found CircleCI, the CI/CD pioneering company.

As for that $3.5 million seed round, it was led by Cervin Ventures, with participation from Boldstart, Data Collective, Harrison Metal, Xfactor (Erica Brescia), Backstage, Nextview, Promus, Correlation, 122 West and Yubari.



from TechCrunch https://ift.tt/2YygRwk
via IFTTT

Comments

Popular posts from this blog

Apple’s AI Push: Everything We Know About Apple Intelligence So Far

Apple’s WWDC 2025 confirmed what many suspected: Apple is finally making a serious leap into artificial intelligence. Dubbed “Apple Intelligence,” the suite of AI-powered tools, enhancements, and integrations marks the company’s biggest software evolution in a decade. But unlike competitors racing to plug AI into everything, Apple is taking a slower, more deliberate approach — one rooted in privacy, on-device processing, and ecosystem synergy. If you’re wondering what Apple Intelligence actually is, how it works, and what it means for your iPhone, iPad, or Mac, you’re in the right place. This article breaks it all down.   What Is Apple Intelligence? Let’s get the terminology clear first. Apple Intelligence isn’t a product — it’s a platform. It’s not just a chatbot. It’s a system-wide integration of generative AI, machine learning, and personal context awareness, embedded across Apple’s OS platforms. Think of it as a foundational AI layer stitched into iOS 18, iPadOS 18, and m...

The Silent Revolution of On-Device AI: Why the Cloud Is No Longer King

Introduction For years, artificial intelligence has meant one thing: the cloud. Whether you’re asking ChatGPT a question, editing a photo with AI tools, or getting recommendations on Netflix — those decisions happen on distant servers, not your device. But that’s changing. Thanks to major advances in silicon, model compression, and memory architecture, AI is quietly migrating from giant data centres to the palm of your hand. Your phone, your laptop, your smartwatch — all are becoming AI engines in their own right. It’s a shift that redefines not just how AI works, but who controls it, how private it is, and what it can do for you. This article explores the rise of on-device AI — how it works, why it matters, and why the cloud’s days as the centre of the AI universe might be numbered. What Is On-Device AI? On-device AI refers to machine learning models that run locally on your smartphone, tablet, laptop, or edge device — without needing constant access to the cloud. In practi...

Max Q: Psyche(d)

In this issue: SpaceX launches NASA asteroid mission, news from Relativity Space and more. © 2023 TechCrunch. All rights reserved. For personal use only. from TechCrunch https://ift.tt/h6Kjrde via IFTTT