Intent Architecture Studio

What It Is

A memory-native analysis application for query opportunity discovery and content architecture. Helps users define durable business context, create scoped analysis runs, discover likely query opportunities, recommend content packaging, derive answer object requirements, and audit existing pages against ideal recommendations. Separates canonical structured knowledge from dynamic run state. Specified for Supabase (PostgreSQL), Next.js, and TypeScript.

Why It Matters

Creating content produces pages. Architecting content systems produces the structural logic that determines which pages should exist and what each must contain. Most content strategists do the first and skip the second.

Most content strategy starts from keywords and works backward to pages -- volume-driven, reactive, structurally disconnected. Intent Architecture Studio inverts this: start from durable business context (company, offerings, dimensions, scopes), discover the query opportunities that structure implies, then architect the content system that serves those opportunities. The result is not a content calendar but a content architecture with explicit requirements for each answer object. The memory-native design is the critical differentiator. Approved learnings persist across analysis runs. The system accumulates organizational knowledge without re-discovery, getting structurally smarter with each engagement rather than starting from zero.

Proof Points

5 detailed specification files: system overview, full build proposal, math/logic/scoring, domain model, Supabase schema
Core design: separation of stable context (company, offerings, dimensions, scopes) from dynamic run state
Memory-native: saves only approved durable learnings to persistent memory -- no noise accumulation
7-step analysis pipeline: business context then scoped run then query discovery then content recommendation then answer objects then page audit then memory update
Domain model: company, offerings, dimensions, scopes, queries, content packages, answer objects, page audits
Specified for Supabase (PostgreSQL), Next.js, TypeScript -- production-ready schema design
Scoring model with mathematical specification for query opportunity prioritization

Market Position and IP

Intent Architecture Studio addresses a gap no existing tool covers: memory-native, structurally-grounded content architecture. SEO tools (Ahrefs, SEMrush, Clearscope) discover keywords by volume. CMS platforms (WordPress, Contentful) manage content after creation. Neither architects the content system from business context through query structure to answer object requirements. The memory-native design creates compounding intelligence across engagements -- each run builds on the last, making the tool more valuable over time rather than resetting to baseline. The mathematical scoring model for query opportunity prioritization provides defensible rigor that keyword volume alone cannot match.

Novel Research Contribution

Existing content strategy research treats content planning as a keyword-driven or audience-driven activity. Intent Architecture Studio demonstrates that content architecture can be derived from business structure -- that the organization's offerings, dimensions, and scopes mathematically imply the query opportunities that content must serve. The memory-native design contributes a pattern for durable learning in analysis tools, where approved insights compound rather than expire.

Implementation and Impact

When built, clients will receive a content architecture engagement delivered through the Studio. The 7-step pipeline produces a query opportunity map derived from business structure, content packaging recommendations with explicit rationale, answer object specifications with completeness requirements, and page audit results showing gaps between existing content and structural requirements. All grounded in the client's durable business context, not keyword volume. Measurable outcome: content strategy derived from structural analysis that compounds across engagements.

Connections

Imperatives: 10x10 Domain Intelligence
Builds: Simiya (shared ontological discovery methodology)
Frameworks: Simiya Methodology
Capabilities: Knowledge Architecture and Ontology