Why We’re Building This: The Foundation of Our Company and Where We're Headed

As we approach launch, I wanted to take a moment to share a bit of the thinking behind our company—why we started it, what drives us, and where we’re headed. This isn't a formal announcement; it's more of a behind-the-scenes look at the motivations that shaped our journey, and a small teaser of what we're building as a product-first infrastructure company.

The initial spark was simple: our customers. Or more specifically, the voice of the customer—a voice that was often overlooked, fragmented, or underserved by the existing landscape of infrastructure solutions. That voice became a source of both inspiration and urgency. It challenged me to ask why things were the way they were, to obsess over how we might do better, and to ultimately define what we could build that would meaningfully solve the problems we kept hearing.

One of those problems, consistently voiced and deeply felt, was around storage—a term so broad it almost loses meaning without context. Some define storage through the lens of protocols: NFS, CIFS, SAN. Others focus on APIs: object storage, database storage, and beyond. Each of these has technical merit, but I found that none of these conversations got to the core issue we were hearing from users.

So we decided to reframe the problem. Instead of debating storage formats or transport layers, we asked a more fundamental question: what do all these systems ultimately try to achieve?

The answer, for us, was persistence.

In the context of modern storage systems, we need persistence to ensure that data remains available, intact, and recoverable in the face of various challenges. Whether it's a file on a hard drive, a database record, or an object in a cloud storage system, persistence guarantees that the information will not disappear when the system restarts or when hardware failures occur. This is critical for everything from day-to-day business operations to more complex use cases like regulatory compliance, disaster recovery, and data analytics.

Now that we've laid the foundation around the concept of persistence, we can start to explore how this principle influences the direction of our technical strategy. Persistence is not just a checkbox—it’s the lens through which we evaluate the value, risk, and complexity of data storage. Once we accepted that persistence is the north star, the natural next question became: Where do we focus our efforts first?

Rather than spreading ourselves thin, we chose to focus on solving one hard problem—a problem that is not only technically challenging, but also growing in urgency and impact. Our philosophy was simple: solve something meaningful and messy first, then iterate forward.

And so, we turned our attention to what we believe is one of the most pressing and unruly challenges in storage today: unstructured data.

Yes—that growing beast that creeps silently across organizations, bloating budgets, straining infrastructure, and giving CIOs and IT leaders sleepless nights. Unlike structured data, which fits neatly into rows, tables, and databases, unstructured data comes in unpredictable formats: documents, images, audio files, videos, logs, sensor outputs, AI-generated content, and more. It's data that doesn’t sit politely in a schema—it sprawls.

With the rise of AI and now AGI (Artificial General Intelligence), this problem is not just growing—it’s accelerating. Some would call it an explosion. Generative models are producing enormous volumes of synthetic data—text, code, images, embeddings—all of which needs to be stored, indexed, accessed, and preserved. The challenge is no longer just about capacity. It’s about scalability, searchability, cost-effectiveness, and governance over a type of data that resists structure by definition.

In short, unstructured data isn’t just a storage problem—it’s a persistence problem at scale. And if we want to build systems that can adapt and endure in this new era of data abundance, this is the kind of problem we have to tackle head-on.

There’s a lot to unpack here—and as we started to seriously examine the problem of unstructured data, its true complexity began to unfold. What initially seemed like a matter of sheer volume quickly revealed itself to be a multi-dimensional challenge. It wasn’t just about storing more data. It was about understanding its dispersity, its distribution, and how those factors amplify the difficulty of managing it at scale.

Unstructured data isn’t centralized, clean, or uniform. It’s scattered—across endpoints, across clouds, across regions, and across applications. It's created by a wide array of sources—human, machine, AI—and it's stored in incompatible formats, governed by inconsistent policies, and accessed through fragmented interfaces. The problem was no longer just about capacity. It had become an equation of:

Scale — how do we handle ever-growing volumes of unpredictable data types?

Distribution — how do we persist and access data that's spread across geographies and platforms?

Source diversity — how do we ingest, normalize, and manage inputs from an ever-expanding set of systems?

Lifecycle and governance — how do we maintain visibility, control, and compliance over data we don’t always "own" or fully control?

This realization gave us a lot to work on—and it forced us to zoom out and look at the problem from a broader, global perspective. We understood early on that unstructured data doesn't live in one place—and that our solution couldn't either. We had to think across silos, departments, data centers, and cloud regions, often crossing geopolitical borders in the process. Cloud storage, while seemingly limitless, brought its own set of constraints—latency, data sovereignty, cost models, and interoperability, to name a few.

This is what began to shape the concepts and ideas that would guide our next steps. We weren’t just solving a technical problem; we were starting to architect a framework for persistent, distributed, unstructured data management—something that could operate globally, flexibly, and securely, while still being grounded in performance and simplicity.

It was the convergence of scale, sprawl, and siloed infrastructure that clarified the path forward: we needed a new way to look at storage—one that treats persistence not just as a feature, but as an end-to-end design principle.

I think this serves as a solid grounding for the conversation we’re just beginning. As we move forward, we’ll start to share more about the work we've been doing—how we're approaching these challenges, what we've built, and why we believe it's the right time to rethink persistent infrastructure from the ground up.

We’re excited to take this journey publicly, and we can’t wait to show you what’s next.

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