Published: October 14, 2025
In partnership with a group of startups in New York City, we hosted an "AI in Action" technical workshop. The goal was simple: demonstrate how client-side AI and built-in AI APIs can be directly integrated into their products for greater speed, privacy, and a better user experience.
In total, we hosted 24 developers from 8 innovative startups. The morning session featured talks from product and engineering experts, covering the immense potential of open source, on-device models and the strategic importance of bringing AI directly to the web platform. Technical specialists then provided practical guidance to get started with the built-in AI APIs.
Attendees found the event to be highly valuable, discovering it was easy to use these APIs regardless of their existing machine learning knowledge. They also discovered new use cases for their applications through experimentation. We were excited to validate our documentation. One group even helped us identify and reproduce a complex bug, so we could submit a fix.
Our attendees successfully developed 10 prototypes using client-side AI. Take a look at some of their projects and learn about their experience at the event.
Adapter's event detection using Prompt API
Adapter's goal is to build "Mission Control for our daily lives enabling maximum free-time not screen-time." They built a proof-of-concept extension with two capabilities:
- Intelligent and aligned event detection which identifies events within a web page while browsing (concerts, restaurants, events) then adapts them with personal context including personal calendar availability, life preferences, and real-time social signals, all processed locally.
- Real-time content reranking that personalizes the ordering of content on a web page to your personal interests on demand.
Adapter used the Prompt API for parsing, reasoning, and calling tools, and the Writer API for local text generation.
"We're doing complex reasoning and multi-step workflows at the edge with limited privacy tradeoffs. This enables personal intelligence applications that were impractical when every inference meant shipping data across networks while deepening remote computation." – Dillon Ponzo, Adapter's founding engineer
Chrome's built-in AI APIs enable lightweight models that process data locally, preserving privacy by default. Adapter's founding engineers Aidan Crank and Dillon Ponzo saw this as validation of their architectural philosophy.
"Most AI extensions capture context and send it elsewhere," explains Crank, who previously worked on large scale ML engineering at AWS prior to joining Adapter. "Chrome's built-in AI inverts that model. Your personal data stays on your device, yet you get intelligent experiences previously unobtainable."
Adapter co-founder Adam Ghetti, whose previous company Ionic Security pioneered autonomous data-centric security at scale, sees deeper implications: "Privacy isn't a feature you add; it's an architecture you choose. Chrome's built-in AI makes that architecture practical."
As Chrome expands these capabilities with multimodal support and richer APIs, the edge isn't just catching up to the cloud. For personal and private AI, it's about surpassing it where it makes sense.
Sublayer categorizes images with the Prompt API to improve variations
Sublayer created a fun app called Photoslider, designed to revolutionize how you interact with and generate variations of your images.
To use PhotoSlider, the user uploads a photo, or captures a new one, and clicks Analyze. The Prompt API sends these images to the model for analysis, requesting the model identify 3 key attributes and give those attributes a value of 1 to 10. For example, an attribute may be "traditional" or "luminosity."
On the frontend, the user is presented with the image and sliders to adjust the values or introduce new attributes with custom values. Requests for changes and the image are sent to server-side AI, so that a larger model with multimodal output capabilities can generate a brand new image based on the changed specifications This iterative process can be repeated endlessly, giving you complete control until you achieve your ideal image.
Scott Werner, CEO of Sublayer, expressed his enthusiasm: "We've been genuinely interested in exploring what local inference looks like. Having it readily available within the browser on our users' machines by default is infinitely easier than relying on users to navigate the complexities of installing models directly."
Echo3D processes 3D models into rich searchable data
Echo3D provides a platform and API for enterprises to seamlessly store, secure, and share 3D models and scans across diverse teams and organizations. Their advanced 3D and text pipelines efficiently process 3D models into rich, searchable data.
At the event, echo3D developed 3D-to-text-to-3D tools that enhance the visual comprehension of assets. They used the Prompt API to automate model tagging, detect duplication, and streamline the cataloging and documentation of extensive 3D libraries.
{
"description": "A 3D model of a large, tan-colored sandcastle with one main
tower, four small towers, and staircases wrapping around. The towers
have multiple windows. There is a main gate.",
"tags": ["sand","castle","gate","tan","tower","staircase"]
}
This gives every asset a rich, consistent, and searchable description, thus making a user's entire library more organized and accessible. Furthermore, it saves storage space and prevents versioning conflicts caused by redundant files.
"Our team truly valued the event. We were particularly impressed by the ease with which AI features can be integrated into web applications using built-in AI. The ability to prototype and deploy secure, client-side AI features in such a short timeframe was a significant advantage." – Alon Grinshpoon, CEO at echo3D
Spot2 created structured metadata from uploaded images
Spot2's application lists real estate properties for rent in Mexico City. Often when these properties are listed, critical metadata and other valuable information is missing from the listing. The details are highly variable, depending on the supplier's attention to detail. Spot2 spent the day enhancing data quality with the Prompt API.
Their team developed a feature to automatically process and organize how listing metadata is structured. This process occurs the moment a photo is uploaded, which helps with completeness and consistency. By performing this task client-side instead of server-side, the feature is cost-effective.
If launched, this feature promises a dual impact: a marked improvement in data quality and a noticeable reduction in operational expenses. "We anticipate that higher quality listings will also translate into an increased conversion rate."
Join us next time
We plan on hosting more AI in Action workshops in the future. Check back in on our blog to get the latest announcements.
- Join the Built-in AI Challenge 2025. We're hosting a virtual hackathon for all developers. Create web applications or Chrome Extensions using built-in AI APIs, for a chance to win one of $70,000 in prizes.