Sonilo and Shutterstock are betting that licensed training data could define the future of AI music.
Updated
May 13, 2026 3:39 PM

A human operating a digital turntable. PHOTO: UNSPLASH
As copyright disputes continue to grow around AI-generated music, Sonilo, the world’s first professionally licensed video-to-music AI platform, has partnered with Shutterstock to train its models on licensed music catalogs.
The agreement gives Sonilo access to Shutterstock’s music library for AI model training. According to the companies, it is Shutterstock’s first partnership with a video-to-music AI platform and the timing is significant. AI music companies are facing growing pressure over how their systems are trained. Artists and record labels have increasingly challenged the use of copyrighted music in AI datasets, especially when licensing agreements or compensation structures are unclear.
That tension has created a divide across the industry. Some companies have continued building models around scraped or disputed data. Others are trying to position licensing as part of the product itself.
Sonilo falls into the second group. The company says its models are trained only on licensed material where artists and rights holders have agreed to participate and receive compensation. The Shutterstock partnership strengthens that position while giving Sonilo access to a larger pool of commercially cleared music.
The collaboration also points to a broader change happening inside generative AI. As AI tools move into commercial production, companies are being pushed to show not just what their models can generate, but also where their training data comes from.
Sonilo’s platform is built around video rather than text prompts. The system analyses footage directly, studies pacing and emotional tone, then generates an original soundtrack to match the content. The company says this removes the need for manual music searches, syncing or editing workflows. The generated tracks are cleared for commercial use across social media, branded content and broadcast production.
Shawn Song, CEO of Sonilo, said: "Music has always been the last unsolved layer of video creation, and video has always carried its own soundtrack. We built Sonilo to hear it and compose from it, without a single text prompt. But how we build matters as much as what we build. While others have chosen to take artists' work without permission and charge creators for the privilege, we've chosen a different path—one where artists are compensated from day one. Partnering with Shutterstock reflects that standard. Every model we train meets a bar the music industry can stand behind, because the most innovative AI platforms don't have to come at the expense of the artists who make all of these possible."
For Shutterstock, the deal expands the company’s growing role in generative AI infrastructure. The company has increasingly focused on licensing content for AI systems across images, video and music.
Jessica April, Vice President of Data Licensing & AI Services at Shutterstock, said: "AI innovation depends on access to high-quality, rights-cleared content and trusted licensing partnerships. Sonilo's approach reflects the growing demand for responsibly sourced training data and commercially safe AI workflows. We're pleased to support companies building generative AI products with licensed content and scalable data solutions that help accelerate innovation while respecting creators and rights holders."
The partnership also comes as Sonilo expands into creator and developer ecosystems. Earlier this month, the company launched as a native node inside ComfyUI, an open-source AI workflow platform used by millions of creators. Sonilo also offers API access for integration into creator tools, video platforms, game engines and other AI systems.
As AI-generated music becomes more common across advertising, creator platforms and digital media, the industry’s focus is shifting beyond generation alone. Questions around licensing, ownership and compensation are increasingly shaping how AI music companies position themselves and build trust with creators.
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Backed by Menlo Ventures, BrainGrid tackles planning gaps as AI makes software building accessible to more founders.
Updated
April 20, 2026 1:40 PM

A phone screen with app icons. PHOTO: UNPSLASH
As artificial intelligence makes it easier to write code, a different problem is starting to surface. Building software is no longer limited by technical skill alone. Increasingly, the challenge lies in deciding what to build, how to structure it, and how to turn an idea into something that actually works.
That shift sits at the centre of BrainGrid, a startup that has raised $1 million in pre-seed funding led by Menlo Ventures, with participation from Next Tier Ventures and Brainstorm Ventures. The company is building what it describes as an AI-powered planning layer for people who want to create software but may not have a technical background.
The timing reflects a broader change in how products are being built. Tools like Claude Code and Cursor have made it possible to generate working code through simple prompts. For many first-time founders, this has lowered the barrier to entry. But writing code is only one part of the process. Turning that code into a reliable product requires structure, sequencing and clarity—areas where many projects begin to fall apart.
In traditional teams, this responsibility sits with product managers who define what needs to be built and in what order. Without that layer, even well-written code can lead to products that feel disjointed or incomplete. Features may not work together, integrations can break and the final product often does not match the original idea.
BrainGrid is designed to address that gap. Instead of focusing on generating code, it helps users map out the structure of a product before development begins. The aim is to give builders a clearer starting point so that the tools they use—whether human or AI—can produce more consistent results.
The company says more than 500 builders have already used it to create software products across areas like fitness, healthcare and productivity. These range from first-time founders experimenting with new ideas to experienced developers working independently. In many cases, the products are already live and generating revenue, suggesting that the demand is not just for experimentation but for building something that can scale.
For investors, the appeal lies in the evolving role of software development. As AI takes on more of the technical work, the value shifts toward defining the problem and structuring the solution. In that sense, planning becomes less of a background task and more of a core capability.
The US$1 million raise is relatively modest, but it points to a larger trend. As more people gain access to AI tools, the number of potential builders expands. What remains limited is the ability to organise ideas into products that work in the real world. If that shift continues, the next wave of software may not be defined by who can code, but by who can plan.