Optimize for LLMs task
Build the evidence AI answers can find, understand, and cite
Audit your discovery footprint, entity clarity, answer structure, authority, and technical signals. Get a prioritized plan for improving visibility across AI search without promises of guaranteed rankings.
62/100
discovery score
4
entity gaps
12
questions mapped
Priority opportunities
Define the category relationship between reporting tools and marketing decision systems.
Publish a source-backed answer to “How should agencies retain campaign context?”
Connect founder, product, category, and customer entities with consistent descriptions.
Marketing Brain context
It starts with what you already know
Maestrix reads reusable strategy objects before it generates. You choose the relevant context for this run.
Brand and entities
The company, product, founders, category, and relationships AI systems should understand.
Positioning
The category and differentiated claim that should stay consistent across sources.
Audience questions
The questions buyers ask while discovering, comparing, and validating options.
Existing content
Pages, guides, proof, and definitions that can become citation-ready answers.
Competitive landscape
The sources and competitors that already shape answers in the category.
Proof and authority
First-party evidence, expert perspective, and credible external sources.
Inside the task
From context to a usable deliverable
- 01
Audit discovery
Assess entity clarity, answer coverage, content structure, authority, and technical access.
- 02
Map questions
Group buyer questions by discovery, comparison, validation, and decision intent.
- 03
Design source assets
Specify pages, evidence, definitions, and citations that strengthen each answer.
- 04
Prioritize the work
Sequence quick fixes, authority building, and ongoing measurement.
The handoff
What one run gives you
Concrete working assets, organized in the same workspace where you generated them.
Discovery scorecard
A current-state assessment across ten AI-search readiness dimensions.
Entity plan
Names, relationships, descriptions, and consistency gaps to resolve.
Question map
Priority questions paired with the page and answer format they need.
Content structure guide
Answer blocks, headings, tables, definitions, and evidence patterns.
Authority roadmap
First-party research, expert sources, mentions, and association building.
Measurement plan
Queries, citation checks, freshness signals, and review cadence.
Why it is different
AI search optimization vs traditional SEO
Traditional SEO often begins with rankings and keywords. This task also maps entities, questions, source authority, and answer structures that AI systems can parse and cite.
- Covers discovery and citation readiness
- Connects every recommendation to buyer questions
- Includes entity and authority work
- No guaranteed visibility claims
Continue the workflow
Fix the website experience behind the answer
Use the Website Grader to prioritize clarity, relevance, proof, friction, and conversion improvements on the pages AI search sends people to.
Questions before you run it
Run it on your brand
See what changes when the AI starts with strategy.
Your first 10 credits are included. No credit card required.