We Built This For Ourselves

After shutting down Double, our direct indexing platform, we found ourselves at an inflection point. Rather than rushing into the next thing, we took time to experiment and explore different ideas.

We believed deeply that deep research is incredibly powerful—the ability to synthesize information from multiple sources, understand context, and provide nuanced answers. But what was the right application? We explored different domains, looking for a problem that truly needed this capability.

Shopping emerged as a compelling use case. The problem space was clear: consumers were drowning in choices, product information was scattered across countless websites, and making informed purchase decisions required hours of research. If we could apply deep research capabilities to shopping, we could genuinely help people make better decisions.

We built a prototype shopping agent. The kind that could shop for very specific things—corner cases with precise dimensions, technical requirements with exact specifications. Not just “find me a laptop” but “find me a laptop with a 14-inch screen, under 3 pounds, USB-C charging, at least 16GB RAM, under $1,500, with good Linux support.”

It worked beautifully in demos. Claude Desktop could understand natural language requests and actually browse product catalogs.

Then we tried it on real e-commerce sites—and realized there were some key gaps missing from making it actually work.

The problem wasn’t that AI couldn’t read product pages—it could. The problem was that when users asked specific questions like “Does this laptop support Linux?” or “Can this camera record in 4K at 60fps?” the answers often weren’t clearly stated on the product page.

Marketing copy focused on vague benefits. Spec sheets listed features but not capabilities. Reviews were scattered and contradictory. The information existed somewhere, but it wasn’t structured in a way that made it easy to answer precise questions with confidence.

Our shopping agent could parse the content, but it couldn’t give definitive answers. It would hedge: “It appears to support…” or “Based on the product description…” Users needed certainty, not qualifications.

That’s when it hit us: this wasn’t just our problem. Every company building AI agents would face this. And every website owner would need to make their content AI-readable if they wanted to stay relevant.

Search traffic is already moving to AI. ChatGPT, Claude, Perplexity—users ask questions there first now. If your content isn’t optimized for AI, you’re invisible.

We needed infrastructure. A standard way to serve AI-optimized content. Something that could sit alongside existing websites without breaking them.

That’s when it clicked: every website needs a way to answer AI’s questions directly—a structured endpoint that serves clean, accurate information instead of forcing AI to parse messy HTML.

We built Pillar to do exactly that. It crawls your website, extracts the important stuff, and serves it through an endpoint that works with ChatGPT, Claude, and other AI platforms. No more guessing from marketing copy. No more uncertain answers.

Our shopping agent could suddenly understand entire product catalogs in seconds. It could answer specific questions like “Does this last 8 hours?” with precision and sources.

But building this infrastructure was still too hard. You needed backend expertise, deployment knowledge, and understanding of how AI consumes content. Most companies wouldn’t tackle it themselves.

So we built Pillar—infrastructure that makes any website readable by AI:

• Crawl your site and auto-optimize content for AI – We transform your existing content into formats that AI can easily understand and process
• Deploy an answer endpoint with zero configuration – Get up and running in minutes, not days, with our automated setup
• Track what buyers are asking and how AI responds – See exactly what questions potential customers are asking AI about your products
• Monitor competitors and optimize your visibility – Stay ahead by understanding how AI represents your competitors

Pillar works with ChatGPT, Claude, Perplexity, and other AI platforms. We built it first for our own shopping agent. Then we realized every website needs this.

We’re betting on a future where AI agents are how people navigate the internet. Not search engines showing 10 blue links. Not even ChatGPT answering questions.

Agents that actually do things: book flights, compare insurance, research products, manage your finances. Agents that need structured, reliable access to information.

Pillar is the bridge. We help websites become AI-native, and we help developers build agents that can actually use the web.

Developer-First, Always

We’re developers building for developers. We care about clean APIs, good docs, and infrastructure that just works. No buzzwords, no marketing fluff—just tools that solve real problems.

Transparent – No hidden costs. No vendor lock-in. No BS.

Developer-First – Built by developers who actually use this stuff.

Join Us in Building the AI-Native Web

Whether you’re building agents or making your site AI-readable, we’re here to help. Get started free and see how Pillar can transform your web presence for the AI era.