We just got accepted into the AWS Activate program. On paper, it’s a nice perk. But for our internal R&D team building spatial apps for social impact, it’s a lifeline. It means we can test heavy machine learning models and render complex 3D environments for our non-profit initiatives without draining our resources. More importantly, it gives us a secure, scalable sandbox to build our tools right.
From Selling Cameras to Spinning Up Servers
Our history with Amazon goes back a few years. Before we were processing spatial data in the cloud, Adostrophe was India’s first authorized Insta360 hardware distributor, handling logistics and selling cameras to early creators.
Spending years navigating Amazon's seller systems made our team comfortable with their interfaces. Today, while our commercial wing focuses on enterprise-grade Matterport 3D scanning, our research division—Adostrophe Labs—is moving deep into cloud infrastructure to power social good applications.
The Activate Advantage for Social Tech
Activate is Amazon’s program designed specifically to help startups scale by providing cloud credits, architecture guidance, and technical support. Learn more about AWS Activate at aws.amazon.com/startups . Programs like AWS Activate, Microsoft Founders Hub, and NVIDIA Inception aren’t here to subsidize our commercial industrial shoots—they exist solely to empower our experimental, social-impact technologies.
For us, AWS absorbs the financial risk of R&D. If an experimental machine learning pipeline for a digital accessibility tool fails, or if a dense 3D render crashes during testing, we only burn our allocated credits, not our operational runway. It gives us the freedom to test advanced infrastructure without the immediate overhead.
Building on Matterport’s AWS Backbone
There is a strategic technical reason we chose AWS for our sandbox. Matterport—the core engine behind all our spatial data captures—runs its massive global cloud infrastructure entirely on AWS. By spinning up our own servers in the exact same ecosystem, we drastically reduce latency when pulling heavy 3D models, point clouds, and spatial data directly from their servers.
This proximity allows us to do far more than just capture and deliver standard virtual tours. We are actively developing custom software workflows using the Matterport API and SDK to manipulate spatial data programmatically.
The Technological Moat
But when you look at what it actually takes to build a scalable, defensible product out of this in the real world, you realize there are no shortcuts. Rendering adaptive 3D worlds on low-end smartphones with spotty internet isn't something you can just "vibe code" or piece together from templates. Achieving true production quality requires deep, intentional engineering.
Every single feature has to be hand-coded from scratch to keep memory usage lean and performance stable under real-world infrastructure constraints, ensuring the app can actually scale to new territories without breaking. This level of optimization is exactly why we currently funnel our AWS credits entirely into the heavy edge ML computes required to make it work for our social-good apps.
While our focus in this sandbox is non-profit, doing things the hard way is how we build our technological moat and stay unique. Right now, we only offer standard, out-of-the-box Matterport tours to our commercial clients. But as we master these complex integrations and harden our mobile infrastructure internally, we are laying the groundwork for our enterprise tier. Eventually, we'll take these battle-tested skills to our commercial servers to offer highly custom, paid enhancements—like deep spatial analytics or AI-driven interactive avatar guides.
Personalized Spatial Worlds in Finostrophe
A major focus for our AWS resources is Finostrophe, a 3D gamified app designed to help users manage their personal finances in regional languages. Storing, processing, and rendering interactive 3D spaces requires immense backend capability.
To make the financial learning experience truly immersive, we’ve developed a feature where Finostrophe users can actually capture and import a Matterport virtual tour of their own real-world environment (like their living room or small shop) to act as their customized 3D financial hub within the app.
Handling this influx of custom user spatial data via the API is exactly why we need AWS. And for users who want a flawless, high-fidelity environment but don't want to scan it themselves, they have the option to hire our commercial scanning team to shoot it professionally for a standard service fee.
Keeping ML Private with Ecostrophe
Beyond Finostrophe, we are heavily invested in Ecostrophe, an accessibility toolkit for blind developers. A major issue with modern AI and developer tools is data privacy. We can't feed sensitive user logic or code into public models. Instead, Amazon Bedrock lets us test foundation models in a completely isolated, secure environment.
The Java Problem for Blind Coders
As we work with AWS and cloud tools, we inevitably run into Java. Java can be frustrating for developers relying on screen readers. The issue isn’t the interface; it’s the code structure. Consider this basic loop:
public class Main {
public static void main(String[] args) {
for (int i = 0; i < 5; i++) {
System.out.println("Processing: " + i);
}
}
}A screen reader linearizes this entirely, reading out every bracket, space, and semicolon in sequence. It makes debugging slow and tedious. With Ecostrophe, we are converting that structure into real-time haptic feedback, letting a developer physically "feel" the code's nesting and hierarchy. Pulling that off without lagging requires significant, low-latency backend computing.
The Multi-Cloud Reality
Adopting AWS doesn’t mean replacing our existing stack. We still rely on Microsoft Azure through the Microsoft Founders Hub and hardware from the NVIDIA Inception Program. AWS simply adds another layer to our infrastructure—a dedicated space to stress-test spatial environments, run private ML workflows, and push our social-good applications forward without compromises. This is the kind of hard infrastructure work that turns experimental spatial tools into products we can actually ship.