Open Web AI Query Architecture

Moving beyond keyword SEO to high-resolution AI conversations. A standardized protocol enabling AI systems to match users with perfect products through natural language understanding.

THIS IS HOW THE OPEN WEB
SHOULD WORK WITH AI

REST API → Not Web Scraping

Click components to explore • Hover to highlight flow

💬

User Query

Natural language request

🤖

AI Assistant

Processes query

📄

llm.txt Discovery

✓ Finds REST API endpoint

REST API Request

✓ Ethical & Fast

🎛️

Business Control

Site Maintains Control

🗄️

Vector DB

Smart Matching

🎯

Product Variations

400+ per product

🔍

Context Matching

Ranks by relevance

Personalized Response

Perfect Match!

WIN · WIN · WIN

A better way forward for businesses, AI systems, and users

🏢

Businesses Win

Authentic Voice: Users get the best version of the answer that you can provide—not AI rewording your message.

Maintain Control: This is what your business thinks based on the query. Your rules, your pricing, your relationships.

Build Relationships: You can't compete on price alone. When AI speaks for you, you lose. When it delivers your voice, you win.

🤖

AI Systems Win

Better Answers: Structured, reliable data means better responses for users—the whole reason LLMs exist.

Quality Training Data: Businesses create 1000+ human-edited, proofed content pieces per product—gold for future model training.

Sustainable Development: This model puts the onus of content development on businesses, who are incentivized to improve quality continuously.

👥

Users Win

Better Product Fit: Context-aware matching means you get products that actually fit your specific needs and situation.

Higher Satisfaction: Authentic business voice and messaging builds trust and confidence in your purchasing decision.

Transparent Information: You know you're getting the business's real perspective, not an AI's interpretation or hallucination.

The old way: AI scrapes websites and speaks FOR businesses
The OWAQA way: Businesses speak directly through structured APIs

See It In Action

Technical Architecture

Core Components

robots.txt + llm.txt

Extended robots.txt convention including llm.txt manifest for AI-readable site summaries, taxonomy, and API endpoints.

REST API Interface

Structured endpoints accepting AI queries with intent, budget, and context parameters, integrated with business MCPs.

Vector Database Matching

Business-maintained vector databases containing micro-targeted product variants optimized for specific contexts and personas.

Security & Attribution

Built-in rate limiting, API authentication, and attribution systems to ensure secure and fair use of business content.

Our Philosophy

One Product, Many Stories

We believe businesses are best positioned to optimize and present their products to different end users - even when those users have vastly different needs.

The Power of Context

Our interactive demo showcases a single product - a professional tennis racquet. While the physical specifications remain identical, the benefits, messaging, and positioning are carefully tailored for different audiences.

Business-Driven Optimization

Businesses understand their products best and can create targeted variations that resonate with specific user segments while maintaining product integrity.

Persona-Perfect Presentation

From high school athletes to weekend warriors, each audience sees the product through a lens that matches their specific needs and aspirations.

Problems Solved

  • Generic product descriptions that don't resonate with specific audiences
  • Lost opportunities due to mismatched product positioning
  • Difficulty in maintaining consistent product information across variations
  • Ineffective AI-driven product recommendations

Try It Yourself

Experience how the same tennis racquet adapts its presentation for different players in our interactive demo.

Launch Demo

AI & Business Control

Deterministic Control in a Probabilistic World

While AI excels at understanding user context, businesses must maintain control over their product messaging.

AI's Probabilistic Nature

  • Generates dynamic, contextual responses based on patterns and probabilities
  • Can produce inconsistent or unexpected messaging variations
  • May not align with brand values or regulatory requirements

OWAQA's Deterministic Approach

  • Pre-defined, business-approved messaging for each user segment
  • Consistent brand voice and product positioning across all variations
  • Compliance with regulatory and legal requirements

The Best of Both Worlds

OWAQA combines AI's ability to understand user context with business-controlled messaging. While AI determines which variation best suits the user, the actual content remains static and business-approved. This ensures perfect alignment between user needs and business messaging, without the unpredictability of AI-generated content.