Substrate Lab, AI Infrastructure Founded by the team from Stripe, Pulumi, and Robust Intelligence, the startup announced an $8 million seed round to provide sophisticated APIs to enable developers to build more modular AI systems and accelerate a new era of software development. The round was led by Lightspeed Venture Partners, with participation from South Park Commons, Craft Ventures, Guillermo Rauch (Vercel), Immad Akhund (Mercury), Will Gaybrick (Stripe), and others. Led by co-founder and CEO Rob Cheung and co-founder Ben Guo, the company also announced the official release of its API optimized for running ensembles of models.
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Substrate raises $8 million to build new modular API for AI: “The tools we've created will enable any company, not just tech giants, to run dozens of branching ML models with a single request,” CEO Rob Cheung said.
“The AI market will inevitably move from training models to using inference to leverage those models, which is a huge market that is currently highly inefficient,” said Nnamdi Iregbulem, Partner at Lightspeed Venture Partners. “Rob and Ben are accomplished engineers with over a decade of experience designing APIs and scaling systems at organizations like Stripe, Substack, and Venmo. They are in a strong position to abstract away the complexities involved in operationalizing the right AI model for the job, empowering engineers to optimize development with advanced tools that were previously only available at large tech companies.”
Today, developers integrating AI have the most success by breaking down a problem into tasks and deploying the best model for each task. However, most developers don't have access to an in-house infrastructure capable of running dozens of AI models in a modular pipeline, so they are forced to either use one large AI model for all tasks or stitch together solutions from various API vendors and GPU service providers. Both approaches result in unreliable, slow, and costly AI applications due to low GPU utilization.
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With Stripe's developer-first strategy in its DNA, the Substrate team is developing powerful AI APIs that leverage curated open-source AI models across multiple modalities, including text, images, voice, and semantic vectors, and optimize these models to run at scale, with a particular focus on how quickly the output of one model can be used as input for another. Substrate's underlying infrastructure is deeply integrated with the SDK, making it easy to create “graph relationships” between models on the Substrate platform, enabling developers to create complex multi-inference AI workflows with just a few lines of code, reducing data round trips and maximizing parallelism. Early customers include Substack and Maven.
“New AI models hold great potential, but the tools available to developers today prevent them from introducing intelligence into software systems,” said co-founder and CEO Rob Cheung. “We built Substrate to make it intuitive for developers to write AI-integrated programs by correlating small semantic tasks and automating work, just like they write any other program. The tools we've created will enable any company, not just tech giants, to run dozens of branching ML models with a single request.”
“We chose to partner with Substrate because we knew they could quickly take advantage of the latest technology. ML Model “We don't need to dedicate significant engineering resources to this task,” said Jairaj Sethi, CTO at Substack. “We've integrated Substrate into our internal systems for content classification and recommendations, as well as creator tools, and we look forward to continuing to explore new use cases.”
“Over the past year, we've been looking at various tools to enhance course recommendations in Maven,” said Maven CTO Shreyans Bhansali. “Substrate is a breath of fresh air because it's a product that's explicitly focused on providing the simplest developer experience possible.”
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