Lightning AI (previously known as Grid.ai) unveiled the groundbreaking Lightning AI platform, backed by a $40 million Series B funding round, that completely reimagines how Artificial Intelligence (AI) products, services, and experiences are built. 

With Lightning AI's new platform and framework, the company is introducing a frictionless way to build AI-powered products and services as apps composed of modular components that are seamlessly integrated and connected.

Serving as the "operating system for AI," Lightning AI's platform ushers in a new era of accessibility and sophistication in the field of AI technology. The platform and underlying framework introduce a novel way to build AI by providing a unified experience that accelerates the deployment of AI technology across academic and enterprise use cases. Amid a fragmented machine learning ecosystem, Lightning AI's suite of extensible open-source components and apps simplifies the underserved space and helps advance the widespread adoption of AI technology.

"Launching this platform is a vital step for our company and the industry," says William Falcon, Lightning AI co-founder and CEO. "From day one, I wanted to reimagine the experience of building artificial intelligence beyond the current surfeit of tools and systems. Until now, there hasn't been a way to build production-grade AI apps that takes into account the entire pipeline from development to production. Current options are limiting, highly prescriptive, and lack the flexibility needed to leverage AI in real-world scenarios. Imagine wanting to make a phone call and you're simply handed the disparate parts that make up a working telephone, hoping that one day you'll be able to make a phone call. Lightning AI takes the principles that have made PyTorch Lightning one of the fastest-growing open-source projects in history - simplicity, modularity, and sustainability - and applies them to the task of unifying the entire AI development and infrastructure lifecycle."

Lightning AI is the culmination of work that began in 2018 at the New York University CILVR Lab (Computational Intelligence, Learning, Vision, and Robotics) and Facebook AI Research. As a Ph.D. student working alongside advisers Kyunghyun Cho and Yann LeCun, William Falcon created and open-sourced the popular PyTorch Lightning framework. The explosive growth of the project within the AI community led Falcon to build a platform and company focused on eliminating barriers to widespread AI adoption.

Grounded in the success of the PyTorch Lightning framework, the company built Grid, a platform for developing and training machine learning models on the cloud. The key to the company's previous successes has been its unique ability to abstract away engineering infrastructure from the machine learning lifecycle while maintaining rigorous flexibility for experts who want full control over what they're building. The Lightning AI platform and framework are powered by these groundbreaking advancements, enabling users to conceptualize, build, and deploy AI technology in a matter of weeks, compared to the months and years it would normally take.

"We are excited about the development Lightning AI is leading by allowing AI-driven applications relevant to specific verticals come to life in a simple way. The partnership will bring further ease-of-use to customers and fit well with AWS's industry, use-case and business problem driven approach," said Dr. Kristof Schum, Global Segment Leader of Machine Learning at Amazon Web Services.

$40M Series B Fuels Lightning AI Platform and Community Growth

This $40 million Series B funding round, led by Coatue with participation from Index, Bain, First Minute Capital, and the Chainsmokers' Mantis VC, brings the total raised to date to $58.6 million. Coatue General Partner Caryn Marooney has joined the board of directors, which also includes Index Ventures Partner Bryan Offutt. The capital will fuel further technology innovation, fund new AI research, and be invested back in the company's growing user community and ecosystem. Lightning AI's mission is to lower the barriers to AI adoption as the global AI market is skyrocketing and on track to exceed $500 billion by 2024. 

"As more companies across every sector leverage AI for crucial functions, they need a solution that makes it simple to consume, train, and use AI while also building applications free from vendor lock-in and specialized AI experts," said Caryn Marooney, General Partner, Coatue. "Coatue immediately saw the potential and significance of Lightning AI's mission to democratize AI. We look forward to supporting William and his team as they write a new playbook for AI deployment."

The Lightning-Fast Way to Build AI Apps

Lightning AI allows researchers, data scientists, and software engineers to build, share and iterate on highly scalable, production-ready AI apps using the tools and technologies of their choice, regardless of their expertise. To solve any kind of AI problem from research to deployment and production-ready pipelines, users can simply group components of their choice into a Lightning App and customize the underlying code as needed. Lightning Apps can then be republished back into the community for future use, or kept private in users' personal libraries.

Lightning AI combines a wide variety of extant tools into a modular, intuitive platform for building AI applications in research, enterprise and personal contexts. It is the foundation of the growing Lightning ecosystem, which provides developers with a suite of ready-to-use tools and required infrastructure and compute resources, as well as community support for building AI applications.

The Lightning AI platform is available now and includes:

• The new Lightning framework, which extends PyTorch Lightning's simple, modular, and flexible design principles to the entire app development process
• A collection of tools and functionalities relevant to machine learning, including workflow scheduling for distributed computing, infrastructure-as-code, and connecting web UIs
• A gallery of AI apps, curated by the Lightning team, which can be used instantly or further built upon
• A library of components that add functionalities to users' apps, such as extracting data from streaming video
• A hosting platform for running and maintaining private and public AI apps on the cloud
• The ability to build and run Lightning Apps on private cloud infrastructure or in an on-prem enterprise environment