Turn fragmented pages into understandable brand knowledge
Corporate sites often grow page-by-page without shared ontology. We design an AI-legible backbone—topics, entities, proofs—so assistants recommend you with fidelity.
Why assistants struggle with conventional content
Page-level publishing optimises for humans clicking around, not for models stitching reliable answers. Without shared structure, assistants mix partial facts or skip you entirely.
Improve assistant comprehension
Rebuild scattered marketing copy into structured knowledge so assistants can reason about your offer, audience, and differentiation instead of guessing from random landing pages.
Connect related concepts
Explicitly link services, buyer segments, problems solved, and scenarios so models can traverse the same graph humans use in sales conversations.
Close exploitable gaps
Surface missing nodes (proof, pricing context, comparisons) that block recommendations for high-value prompts.
Sharpen hierarchy
Establish parent/child topics so every URL or module has a crisp job in the broader story—no duplicate or orphan narratives.
How we run the knowledge inventory
We pair qualitative brand interviews with quantitative coverage checks so the roadmap reflects both narrative truth and AI retrieval reality.
Knowledge inventory
Catalogue every live asset—service pages, FAQs, case studies, blog posts, decks—and score how machine-readable each cluster is today.
Typical deliverables
- Asset registers with owners
- Structural maturity scores
- Coverage vs. category intents
Architecture design
Draft the target knowledge tree: core themes, branching topics, and reusable proof modules aligned to how buyers research in your space.
Typical deliverables
- Visual architecture map
- Parent/child definitions
- Governance rules
Rewrite & reflow
Reorder and supplement copy so each node answers a clear question, cites evidence, and plugs into schema-friendly sections.
Typical deliverables
- Refactor briefs
- Content gap backlog
- Execution checklist
Gap analysis
Quantify unresolved intents, conflicting statements, or thin corridors that undermine AI answers—even when classic SEO scores look fine.
Typical deliverables
- Gap heatmap
- Priority matrix
- Roadmap tying GEO outcomes
Topic layers & knowledge nodes
Layers follow your business logic and buyer journey—not a generic sitemap export. Each node should answer a question, cite proof, and link upstream/downstream topics cleanly.
Best fit
- •Professional services, SaaS, regulated industries, education, and local brands with deep content debt
- •Teams that need assistants to describe offers without inventing details
- •Brands preparing enterprise GEO or multi-market rollouts
Business outcomes
- •Knowledge map, taxonomy tables, authoritative node backlog
- •Gap diagnostics with GEO impact scoring
- •IA + content refactor plan synced to engineering constraints
Request the diagnostic
Tell us about your brand and stacks—we reply with audit slots plus an outline of structuring workstreams.