How an AI System Creates and Monetizes Search Patterns for User Interaction
This patent describes an AI system that uses a neural network to understand information, create optimized search patterns from human knowledge, and then uses those patterns to interact with users and make money.
Original patent title: “Site rank codex search patterns”
This patent describes an AI system that uses a neural network to understand information, create optimized search patterns from human knowledge, and then uses those patterns to interact with users and make money. Granted in 2026.
Coverage
What does this patent actually cover?
Based on the abstractabstractA short summary at the front of the patent describing the invention. Not legally binding.Read more →, a "Codex system" of computers, linked into a neural network, continuously scans and gathers information from its environment, understanding and interacting with it. An "optimizer software" then executes instructions based on rules of grammar and semantics to search an "encyclopedia of human knowledge," transforming input into a "search pattern." The system then monetizes and commercializes each transformed input and its optimal output. Finally, an artificial intelligence interaction software, called a "virtual maestro," uses this search pattern and optimal output to engage in scripted communication with the end user. For example, a user might ask a complex question, and the Codex system would process it, find the best answer from its knowledge base, and then have the virtual maestro deliver a tailored, monetized response.
The gap
What does this patent NOT cover?
- Does not cover systems that do not specifically use a neural network for continuous information gathering and environmental interaction.
- Does not cover AI systems where an optimizer software does not apply rules of grammar and semantics to an "encyclopedia of human knowledge" to create search patterns.
- Does not cover systems that do not explicitly monetize and commercialize each transformed input and its corresponding optimal output.
- Does not cover user interaction that is not specifically "scripted communication" delivered by an "artificial intelligence interaction software" referred to as a "virtual maestro."
- Does not cover search or interaction systems that do not specifically interact with an "encyclopedia of human knowledge."
These exclusions are unique to PatentBrief — derived from the actual claim language, not patent-office boilerplate.
Key facts
What made this novel
The clever bit is the integration of continuous environmental scanning with an optimizer that applies grammar and semantics to human knowledge, specifically for generating "search patterns" that are then monetized. This system also introduces a "virtual maestro" for scripted user interaction, creating a complete, self-contained, and monetizable AI information delivery loop.
Schematic visualization of the patent's claim structure. Hand-drawn diagrams in progress for each landmark patent.
Where you've seen this
Real-world examples
Advanced AI search engines with built-in monetization
Automated customer service bots with transaction-based charges
Personalized AI tutors that charge per interaction
AI-driven content recommendation systems with direct revenue streams
Why it matters
The bigger picture
If implemented, this type of system could significantly change how information is accessed and monetized online. By creating optimized search patterns and using a 'virtual maestro' for scripted communication, it could offer a highly structured and potentially profitable way to deliver information to users. The focus on monetizing each interaction suggests a new business model for AI-driven information services.
Filed
July 30, 2023
Granted
September 15, 2026
Market context
Who's building on this
Companies in this space
Major technology companies like Google, Microsoft, and OpenAI are actively developing advanced AI systems for information retrieval and user interaction. Startups focused on AI-driven content generation, personalized learning platforms, and intelligent virtual assistants are also working in related areas, aiming to create more sophisticated and commercially viable AI interactions.
Market impact
As this patent is not yet granted, it has not had a market impact. However, if such a system were widely adopted, it could establish a new paradigm for monetizing AI-driven information services, potentially creating a new category of 'pay-per-insight' or 'monetized interaction' platforms. It could also influence the development of AI agents designed for highly structured and commercially optimized user engagement.
Claim 1 — Plain English
What this patent covers
Based on the abstract, a "Codex system" of computers, linked into a neural network, continuously scans and gathers information from its environment, understanding and interacting with it. An "optimizer software" then executes instructions based on rules of grammar and semantics to search an "encyclopedia of human knowledge," transforming input into a "search pattern." The system then monetizes and commercializes each transformed input and its optimal output. Finally, an artificial intelligence interaction software, called a "virtual maestro," uses this search pattern and optimal output to engage in scripted communication with the end user. For example, a user might ask a complex question, and the Codex system would process it, find the best answer from its knowledge base, and then have the virtual maestro deliver a tailored, monetized response.
The clever bit
The clever bit is the integration of continuous environmental scanning with an optimizer that applies grammar and semantics to human knowledge, specifically for generating "search patterns" that are then monetized. This system also introduces a "virtual maestro" for scripted user interaction, creating a complete, self-contained, and monetizable AI information delivery loop.
What it does not cover
- Does not cover systems that do not specifically use a neural network for continuous information gathering and environmental interaction.
- Does not cover AI systems where an optimizer software does not apply rules of grammar and semantics to an "encyclopedia of human knowledge" to create search patterns.
- Does not cover systems that do not explicitly monetize and commercialize each transformed input and its corresponding optimal output.
- Does not cover user interaction that is not specifically "scripted communication" delivered by an "artificial intelligence interaction software" referred to as a "virtual maestro."
- Does not cover search or interaction systems that do not specifically interact with an "encyclopedia of human knowledge."
Patent timeline
Application submitted to the patent office
Patent officially issued
PatentBrief Score
Impact Score
Early stage
Citation count
0/40
No citations yet
Claim breadth
0/20
Narrow claimsclaimsThe numbered statements at the end of a patent that legally define what the inventor owns.Read more →
Recency
20/20
Granted within 5 years
Assignee scale
0/20
Independent or smaller assigneeassigneeThe entity that owns the patent — usually the inventor's employer or a company.Read more →
PatentBrief Impact Score — based on citation count, claim breadth, recency, and assignee scale. Not a legal assessment.
Heuristic Value Estimate
What this patent might be worth
$19K – $61K
Midpoint $38K · 16.8 yr remaining · industry ×1.6
Heuristic only — blends forward/backward citation counts, claim scope, time remaining, litigation history, and CPC-derived industry baseline. Real valuations need a professional appraisal.
Claim text not yet imported for this patent
Concepts involved
Cite this patent
(2026). How an AI System Creates and Monetizes Search Patterns for User Interaction (U.S. Patent No. 12,737,353). U.S. Patent and Trademark Office. https://patentbrief.org/patent/us/12737353/site-rank-codex-search-patterns
Auto-generated from the patent record. Double-check author order and the issue date against the official USPTO document before submitting.
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Common Questions
Frequently Asked Questions
What does How an AI System Creates and Monetizes Search Patterns for User Interaction cover?
This patent describes an AI system that uses a neural network to understand information, create optimized search patterns from human knowledge, and then uses those patterns to interact with users and make money.
When does this patent expire?
This patent is expected to expire on September 15, 2046, when the invention enters the public domain.
What problem does this patent solve?
If implemented, this type of system could significantly change how information is accessed and monetized online. By creating optimized search patterns and using a 'virtual maestro' for scripted communication, it could offer a highly structured and potentially profitable way to deliver information to users. The focus on monetizing each interaction suggests a new business model for AI-driven information services.
What does this patent NOT cover?
Does not cover systems that do not specifically use a neural network for continuous information gathering and environmental interaction.
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