Sharper Vision.
Faster Execution.

Brand Simplification

Two domains. Clear purpose.

Early last year, as we prepared to launch our web intelligence tools for B2B, we introduced Prism under prism.uprock.com, along with a stack of subdomains to segment products and users.

The idea was clean separation between community and enterprise. In practice, it diluted our brand identity and confused our customers.

The line between consumer and prosumer is almost gone. Power users behave like developers. Developers behave like operators. Everyone uses AI.

We overthought it. Now it is simple. .com is community. .ai is infrastructure.

UpRock.com is the community and network.
UpRock.ai is the infrastructure for builders and agents.

One brand. Two domains. Clear purpose.

The Uptime Experiment

Billions of speed tests. We built uptime.

Our DePIN network was already generating massive observability data, so uptime felt like a natural extension. We partnered with Checkmate, built polished status pages and dashboards, and treated it as a complementary revenue stream while we worked toward the broader vision of a knowledge abstraction layer for the AI web.

At the same time, we were still building the core pieces we truly needed: orchestration, a resilient crawler API, edge case handling, heavy tasks, multimodal support. Uptime helped us harden that infrastructure.

But it also pulled us into a crowded, entrenched market that was not our end game and that caused to spend too much time on the wrong things.

The Realization

People don't live in dashboards

Users only log in when things break. They live in Slack, email, and their workflow tools. "Hey, site is down." Then they expect AI to diagnose it, explain it, and help fix it. That is the real interface.

We learned the hard way that we over engineered parts of our uptime product. We poured time into polished dashboards and complex UI states, when the real value was always the underlying signal. If the data is accurate, structured, and delivered in context, AI can render it however each user prefers. The future UI is personalized and on demand.

The durable asset is the content and the confidence behind it.

New Distribution Model

API. MCP. Chat. That's it.

Cutting is painful. Every founder knows how hard it is to kill something you invested time, money, and pride into. But cutting is part of the process. Adapt or die. The real clarity only comes when customers use the product. That is when distractions become obvious.

We sharpened our view of who the customer actually is and how they work. Developers want clean docs and reliable APIs. Agents want MCP and CLI native tools. Humans are shifting toward natural language interfaces powered by AI. That changed everything.

No sunk cost thinking. If it is built for humans browsing instead of agent execution, it is the wrong abstraction.

The 100x Question

We don't build to be 2x better.

We are a team of serial founders. Our bias has always been to think big or go home. We take real risks and aim to build ambitious systems. A 2x improvement on an existing product might be a solid business, but it is not why we started UpRock.

There are thousands of scrapers on GitHub. So we had to ask ourselves: are we just a DePIN powered crawler? Is that truly 100x better, or just incrementally different?

That question pushed us further. The solution to the problems we're solving is not another scraper. It is reinventing the Insight Engine for the age of human and agent collaboration.

The Insight Stack Primitive

The new unit of web intelligence.

AI does not need more disposable page scrapes. It needs intelligence that persists, compounds, and can be shared and verified across agents and teams.

One off extraction is table stakes. Building durable, structured knowledge that improves over time is the hard part. It is also the risk and the opportunity.

The TAM Explosion

Vibe Research is the new Vibe Coding.

Vibe coding expanded the total addressable market for apps by making software creation easier. That shift is profound. Vibe research does the same for web intelligence. When intelligence becomes structured, persistent, and reusable, every app and every agent suddenly becomes more capable.

Execution Speed

Maestro: Our open-source engine.

As we kept iterating, one thing became clear. The only way to find the right abstractions for the AI web was to fully embrace AI inside our own workflows. Not as a feature, but as a mindset.

By building with agents every day, across models, across tasks, across research and engineering, we started seeing the gaps. Where context breaks. Where knowledge gets lost. Where workflows do not compound. Those daily frictions are what led us to Insight Stacks.

To support that internally, we built Maestro.

Maestro is our multi agent, multimodal orchestration engine. It coordinates many agents and many models across complex workflows, the same architecture that powers Insight Stacks.

We use it ourselves. It helps run our dev workflow, research, crawling, synthesis, and execution layers. Then we open sourced it. If we are building for the AI web, our own stack has to live there first.

Our Decision Framework

The wrong abstraction.

Before agents were mainstream, before MCP, before native agent payments like x402, the obvious output of our infrastructure looked like tools and dashboards for humans, enhanced by AI. That was the default pattern across the industry, and we followed it for a while.

But as the ecosystem evolved, it became clear that this was the wrong abstraction. The AI web does not want polished interfaces. It wants structured outputs, portable context, and machine native primitives that agents can call, remix, and pay for directly.

So we cut aggressively. Anything optimized primarily for human browsing instead of agent execution was reconsidered. No sunk cost thinking. If it did not strengthen the core primitive for the AI web, it did not survive.

The Vision

Knowledge Abstraction Layer