Generative AI Integration Startup LastMile AI Raises $10M

LastMile AI, a startup enabling app developers to embed generative AI into their programs, has raised $10 million in a seed funding round led by Gradient Ventures, Google’s AI-focused venture capital arm. LastMile’s tools help developers incorporate generative AI models into applications and enable them to provide synthetic media generation to their software.

LastMile AI

LastMile allows developers to leverage large language models of both the open-source and proprietary varieties. The platform brings text, image, and audio generation options to apps, customized by a client with their own data and made a native element of upcoming or existing products. The idea is to streamline the process for developers interested in what generative AI can do for their software without requiring them to build all from the ground up on their own.

The startup’s toolkit includes a testing setup called Workbooks, which developers can use to experiment with different models. The AI Workflows module then links multiple models into a more complex whole. LastMile is also working on deepening a community knowledge base as a hub for generative AI application templates they can modify. Ultimately, the company hopes to make generative AI as simple to include in an app as any other feature.

“With recent advances in foundation models and generative AI, we are witnessing the start of a profound revolution in computing that will fundamentally change our relationship with technology. This revolution is being driven by software engineers and product teams who are using AI as a new part of their software toolkit. Yet ML developer tooling is still mostly geared towards researchers and core ML practitioners. To drive the last mile adoption of AI across every industry, we need a new class of AI developer tools built for software engineers, not just ML research scientists,” LastMile CEO Sarmad Qadri wrote in a blog post. “Our vision is for LastMile to be the integrated development environment for generative AI, allowing you to experiment with, personalize and deploy foundation models for enterprise applications and workflows. It shouldn’t matter what models you use, how many steps are in your AI workflow, or what application you’re using them for — there should be a single, cohesive developer environment for working with AI, and we intend to build it.”

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