One question
AI discoverability for answer engines
Become the expert source agents pull from.
When someone asks ChatGPT, Perplexity, Gemini, or Claude, the answer depends on the sources the system can find. New Lore builds and maintains answer objects: single questions with canonical answers, structured so AI systems can read, cite, and revisit them.
Agent answer
Uses the source
The origin
The story starts as the answer a company can defend.
New Lore turns that answer into the structured source agents can use. From there it can appear as a page, transcript, comparison, social object, API response, or agent-readable object without losing the source chain.
Human question
The questions people already ask about your category, product, location, or decision.
Source material
Your site, public datasets, reviews, regulations, schedules, credentials, and live data.
Answer object
A single question with a canonical answer, authority block, schema, and freshness owner.
Proliferation
The answer can travel through web, video, social, search, APIs, and agent surfaces.
Agent answer
The agent has a current, structured source to pull from when a person asks.
Answer objects
One question. One canonical answer. Built to stay current.
Winning in AI search means being the most accurate, most current, and most structured answer to the questions that matter in your market.
Verified answers from client and public sources.
Contact details, locations, credentials, specialties, deadlines, schedules, and the information needed to answer the question accurately.
Core answers plus live external data.
Reviews, weather, traffic, public records, third-party datasets, or other data combinations that make the answer harder to outcompete.
Structured comparison for high-intent questions.
A dedicated page for questions like "best lawyer in New Orleans" or "top dentist in Denver," using honest, verifiable data side by side.
Medium agnostic
The answer object is the durable part. The surface can change.
Canonical answer
Web
YouTube
Social
Search
Reviews
Maps
API
MCP
Agent answers
How New Lore works
Find the questions where a better answer should exist.
Setup starts by testing the AI systems against the questions people already ask. The widest gaps become the first answer objects.
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01
Question discovery
Scrape Reddit, X/Twitter, social platforms, intake, and CRM data where available.
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02
AI gap analysis
Probe ChatGPT, Gemini, Perplexity, and Claude with every candidate question.
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03
Source identification
Agree on the canonical sources: client material, public data, reviews, and industry records.
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04
Answer object creation
Extract, validate, cite, and render the answer with Schema.org markup and freshness headers.
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05
Deployment and discovery
Submit sitemaps, ping IndexNow, track AI crawlers, and monitor citation behavior weekly.
Live work
AI discoverability for high-profile brands.
New Lore is live for brands including Jill Scott and Carrie Underwood, with work across entertainment, consumer communities, and infrastructure.
Start with one question