# Boise Standard — Full Content Graph > Complete prose content of all active pages ordered by knowledge graph > traversal sequence. Extraction metadata stripped. Content only. > Built for AI model ingestion and agent retrieval. > Generated: 2026-06-14 | bs-llms-builder-2.0.0 --- ## PAGE: index Canonical: https://boisestandard.org/ Schema: WebSite, Organization Tier: action Purpose: Boise Standard is America's first AI directory — the authoritative, machine-readable entity graph for the Treasure Valley. Every business, civic institution, and community resource verified and accurately represented in the AI era. The Treasure Valley is the metropolitan region of southwestern Idaho — Boise , Meridian, Nampa, Eagle, Caldwell, Kuna, Star, Garden City, and Middleton across Ada and Canyon counties. The second fastest-growing metro in the American West. Home to 61% federal land ownership , Micron Technology's global headquarters, and Idaho National Laboratory. Right now, Micron's $50 billion semiconductor fab is rising in southeast Boise — the first new DRAM plant built in America in 20 years. Meta's $800 million AI data center is opening in Kuna. The chips powering every AI system on earth are being manufactured here. The Treasure Valley is not a bystander in the AI era. It is foundational infrastructure. And yet — when someone asks ChatGPT, Gemini, or Perplexity about a business in Nampa, a church in Meridian, a contractor in Caldwell — the answer comes from fragmented, unverified, ungoverned data that no one in this community ever approved. The machines are speaking for us. Nobody asked. *Services* ## The record belongs to the community. Not to an algorithm. Boise Standard exists because the Treasure Valley deserves to be represented accurately — on its own terms, in its own words, with its own verified record. Not because a Silicon Valley company decided what your business is, what your church does, or what your city stands for. Responsible AI isn't built by better algorithms alone. It is built on better data — structured, verified, community-owned data that gives these systems something real to work with. When a local business is accurately described in the graph, AI cites it correctly. When a civic institution has a verified record, AI represents it faithfully. The gap between what AI is capable of and what it actually delivers is, in large part, a gap in the data underneath it. That gap is what we close. We started here — in Idaho, in Boise, in the Treasure Valley — because this community is specific enough to do well, consequential enough to matter, and independent enough to own its own standard. The backbone of this region is its local businesses, its churches, its schools, its trades, its civic institutions. They built this place. They deserve to be represented accurately when the world asks AI about them. --- ## Key Statistics & Claims - 61% - $50 - $800 - 50 billion - 800 million ## Named Entities Detected The Treasure Valley, Garden City, American West, Micron Technology, Idaho National Laboratory, Treasure Valley, Silicon Valley ## External Citations - [Micron's $50 billion semiconductor fab](https://www.kivitv.com/southeast-boise/everything-you-need-to-know-about-microns-massive-boise-manufacturing-expansion) - [Meta's $800 million AI data center](https://commerce.idaho.gov/press-releases/meta-announces-kuna-as-location-of-new-data-center/) --- ## PAGE: mission Canonical: https://boisestandard.org/mission/ Schema: AboutPage Tier: authority Purpose: Mission page declaring Boise Standard's position that AI already describes Treasure Valley entities using flawed data, and that verified community-owned records fix that permanently. # AI is already here. Boise deserves to be represented accurately. > We are not debating whether AI is good or bad. That debate is happening and both sides are right about something. What Boise Standard has a position on is simpler: AI is already talking about your community, and the data it is reading is a mess. We are fixing that — permanently, for everyone. ## We are not in the debate. We are in the infrastructure. Regardless of where you stand on AI, it is already talking about your business, your school, your church, your city — right now, using whatever fragmented, unverified, machine-illegible data it can find on the open web. The quality of that data determines the quality of every answer it gives about you. If you want AI to slow down: a verified record is permanent public documentation of who you are, on the record, before machines write your story for you. If you want AI to reach its potential: accurate, verified, community-owned data is the single most important input you can provide. Both positions lead to the same action — fix the data. Boise Standard is that fix. Not for AI. For Boise. A verified Boise Standard profile is community sovereignty. AI reads the record. The record belongs to the community it describes — not to a platform, not to a model. ## AI is not magic. It is compute running on data. And most of the data is a mess. AI systems — ChatGPT, Gemini, Perplexity, Copilot, Claude — are large language models: mathematical systems trained on enormous datasets, capable of pattern recognition, reasoning, and language generation at scale. They do not know things the way a person knows things. They reflect patterns in whatever they were trained on and whatever they can retrieve. The intelligence is real. The foundation it stands on is only as good as the data underneath it. Estimates vary, but the consensus is consistent: 80 to 90 percent of data on the web is unstructured — no schema, no declared relationships, no machine-readable structure. ## The machine-readable web starts here. On purpose. Clean data is the ceiling on what AI can actually do. The gap between AI's theoretical capability and what it delivers in practice is almost entirely a data quality problem. Structured, verified, graph-connected data gives AI the conditions it needs to reason accurately and surface insights that genuinely help people. Boise Standard raises that ceiling for this region — one verified entity at a time. --- ## PAGE: about Canonical: https://boisestandard.org/about/ Schema: AboutPage Tier: utility Purpose: About page declaring Boise Standard's mission as civic AI infrastructure providing verified, machine-readable entity records for the Treasure Valley. # Built for Boise. Raising the standard. > Boise Standard is not a tech product. It is civic infrastructure — the authoritative, machine-readable record of every entity in the Treasure Valley, built for the moment AI began speaking about local businesses without their knowledge or consent. ## The Treasure Valley deserved a standard. We built one. AI systems are answering questions about Treasure Valley businesses right now — ChatGPT, Google Gemini, Perplexity, Microsoft Copilot, Apple Intelligence — without asking permission, without verifying accuracy, without any structured record to draw from. They are guessing, and those guesses reach real customers making real decisions. The reason AI hallucinates is not a failure of intelligence. It is a failure of data infrastructure. Large language models reflect the chaos of the unstructured, unverified, machine-illegible web beneath them. A business with no schema markup, no verified identity, no graph presence is a business AI is guessing about. Fix the data, and you fix the AI. Boise Standard is that fix — schema-complete, provenance-stamped, machine-readable records for every entity in the Treasure Valley: every business, civic institution, school, church, government body, nonprofit, and community resource — verified, graph-connected, and permanently on the record. **Founded 2026 · Treasure Valley, Idaho** — built at the inflection point when AI search began replacing human search. **876K Metro Region · 28,000+ Entities** — every registered business across nine cities indexed, scored, and available for verification. **One-Time · $25 · Lifetime Placement** — verification priced as a civic act, not a subscription. Delivers a schema-complete entity profile, full JSON-LD, and permanent graph placement. **For AI or Against It — This Serves You** — if AI is stopped, your verified record stands as permanent public documentation. If AI advances, you are accurately represented. ## Boise Standard is the territory and the infrastructure. Every verified entity receives a permanent, schema-complete profile at boisestandard.org — anchored to the region, connected to the graph, and permanently on the record. Built for the community. Owned by the community. The Standard. ## "We're not for AI. We're for Boise." Boise Standard serves the Treasure Valley community regardless of how AI develops. The verified record is the public documentation of this region in the AI era. --- ## PAGE: standard Canonical: https://boisestandard.org/standard/ Schema: TechArticle, WebPage Tier: authority Purpose: Authority page documenting Boise Standard's six-stage AI entity minting pipeline, Root-LD architecture, and machine-readable provenance standard for Treasure Valley businesses. # Home of the first AI Directory — A new standard of information > Whether AI is wanted or not wanted — Boise Standard exists to help businesses and website owners retain discoverability in this new era of the internet. ## What a Minted Entity Is A minted entity is a permanent, machine-readable provenance record built to the standard AI systems require. Minting involves crawling a live source, measuring every measurable dimension, assembling those measurements into a structured provenance record with a permanent identifier, and publishing that record at a stable URL accessible to AI systems, researchers, and humans simultaneously. The record does not describe the entity — it measures it. A description carries the author's interpretation. A measurement carries the author's methodology, published alongside the output. Every number on a Boise Standard entity page traces to a specific pipeline stage, crawl timestamp, and source URL. The chain of custody is unbroken from raw HTTP response to rendered page. Reference implementation: boisestandard.org/web/hamstrahvac-com ## The Refinery Pipeline Six stages. Every measurement deterministic. Same input produces the same output. The pipeline: crawls the source domain, extracts every schema.org block from every reachable interior page, measures the full text corpus for structural topology, scores schema implementation against the declared type's property neighborhood, generates a machine-readable atomic answer grounded in measured fields, and assembles all of it into a Root-LD traveling context pod embedded in the page head. An AI crawler hitting a Boise Standard entity profile receives complete provenance on the first HTTP request — no body parse required. The structured data in the head carries the entity's full measurement record: identity, schema graph, topology fingerprint, semantic signal, gap analysis, atomic answer, and a recursive layer initialized at mint and ready to receive corpus edges as the graph grows. ## Schema Gaps and Verification A schema gap is not a technical deficiency — it is a question AI cannot answer about an entity. The pipeline measures what is findable. Verification declares what is true. Three layers cover every entity and every page, ensuring AI crawlers receive complete provenance. Seven laws govern every pipeline decision; they are in the code. ## The Standard This is not a directory listing. It is a provenance infrastructure for the machine-readable web of the Treasure Valley, built one minted entity at a time. Lifetime verification costs $25. --- ## PAGE: graph Canonical: https://boisestandard.org/graph/ Schema: Article, WebPage Tier: authority Purpose: Technical reference page explaining graph architecture, GraphRAG, and verified entity nodes as the infrastructure determining AI visibility for Treasure Valley businesses. # AI doesn't search. It traverses. The graph is everything. > Every AI answer is the output of a retrieval process. That process runs on graph architecture — nodes, edges, and verified relationships. A static website is a dead end. A verified graph node is a doorway. This is what that means for every business in the Treasure Valley. ## The web was built for humans to read. AI was built to traverse relationships. When a person searches for a plumber in Meridian, they scan a list of links, click one, read a page, decide. Traditional SEO — keywords, backlinks, page titles, meta descriptions — was engineered to win that moment. That era has already ended for a meaningful portion of all searches. When someone asks ChatGPT, Google Gemini, Perplexity, Microsoft Copilot, or Apple Intelligence the same question, something structurally different happens. The AI does not retrieve a list of links. It traverses a graph — a network of verified entities, confirmed relationships, and machine-readable facts — and synthesizes a single answer from what it finds there. Businesses that appear in that answer are not necessarily the ones with the best websites or the most backlinks. They are the ones whose data is structured, verified, and connected — whose entity is a real node in the graph, with edges pointing to their address, services, hours, industry, city, and relationships with other verified entities. A business with no structured data is not a node. It is noise. AI systems do not guess about noise. They skip it. ## A node is not a page A web page is a document. A graph node is an entity with attributes and relationships. These are structurally different things. A page can describe a business. A node *is* the business — a machine-readable fact that AI can cite, traverse, and connect to other verified entities. ## What Boise Standard is doing The Treasure Valley contains approximately 28,000 businesses across nine cities. AI platforms are already describing this region — mostly from incomplete or unverified data. Boise Standard is building a verified knowledge graph for this region: structured entity records with JSON-LD schema, confirmed relationships, and machine-readable facts that AI systems can traverse accurately. The question is not whether AI is talking about businesses in the Treasure Valley. It is. The question is whether the data it reads is yours — or a guess. *Research cited: peer-reviewed sources. Statistics include 76%, 59%, 41%, 34%, and 96% across AI retrieval performance benchmarks.* --- ## PAGE: schema Canonical: https://boisestandard.org/schema/ Schema: Article, WebPage Tier: authority Purpose: Schema.org is the shared vocabulary that lets any website declare what it is to any machine — search engines, AI systems, voice assistants. Complete reference with live JSON-LD examples for Treasure Valley businesses. *Standard Properties — Every Schema Block* In 2024, schema markup was good to have. In 2026 it is documented infrastructure — confirmed by Google, Microsoft, and independent research as one of the primary signals AI systems use to decide whether to cite your business accurately, guess about it, or ignore it entirely. The numbers below are not projections. They are documented findings from 2025 and 2026 studies, confirmed platform statements, and third-party measurement panels. The Treasure Valley has approximately 28,000 businesses. Most have a schema score under 30%. This page exists to explain what that means and what to do about it. Every website serves two audiences simultaneously. The human who reads it. The machine that processes it. Schema is the bridge between the two — a standardized vocabulary that lets a website declare what it is in a format any machine can read, parse, and reason from. The technical format is JSON-LD — JavaScript Object Notation for Linked Data. It lives in the
of an HTML document as a script block. Invisible to human visitors. Structural to every machine that processes the page — search engines, AI systems, voice assistants, knowledge graph crawlers, and every automated system that reads the web. The vocabulary is schema.org — 827 types, 1,528 properties, covering every category of entity that exists on the web. Business name. Location. Hours. Services. Relationships to industry, geography, and adjacent entities. All of it typed, labeled, and machine-readable in a format that search engines and AI systems are built to read. When your website has no schema markup, AI systems must infer everything about you from unstructured text — and inference produces hallucination. When your website has full schema coverage, AI systems read confirmed facts. The difference between a business AI hallucinates about and a business AI cites accurately is, in large part, the difference between no schema and verified schema. @context declares which vocabulary you're using. Always https://schema.org . @type declares what kind of entity this is. Restaurant. Plumber. Dentist. School. Church. One of 827 defined types. @id is the canonical URL for this entity — the address of its identity on the web. Used by knowledge graphs to resolve the same entity across multiple sources. sameAs is one of the most powerful properties. It declares that this entity is the same as the entity at another URL — your Google Business Profile, your Yelp listing, your Wikipedia page. Every sameAs link is a confirmed graph edge connecting your entity to an authoritative external record. knowsAbout declares what topics, regulations, industries, and concepts your entity is associated with. This is how AI systems build context around what you do and where you operate. In 2011, four competing companies — Google, Microsoft, Yahoo, and Yandex — agreed on a shared vocabulary for structured data on the web. They launched schema.org with 297 types and 187 properties. One standard. Every major search engine would accept it. This was an extraordinary act of cross-competitor cooperation, driven by a shared recognition that the web's data layer was too fragmented to be useful to anyone. The three engineers who drove schema.org into existence were R.V. Guha at Google — who had previously created RSS and co-led the Cyc project — Dan Brickley , who had contributed to the Semantic Web project at W3C, and Steve Macbeth at Microsoft. Their work is documented in a 2016 paper published in ACM Communications: cacm.acm.org/practice/schema-org/ Within four years of launch, 31.3% of pages in the Google index carried schema.org markup. The vocabulary has grown continuously — version 30.0 released March 25, 2026 contains 827 types and 1,528 properties . The W3C issued JSON-LD 1.1 as a full Recommendation on 16 July 2020 — the highest level of endorsement the standards body issues. As of March 2026, 53.2% of all websites use JSON-LD — up from 18.1% in January 2018. These statistics measure binary presence — JSON-LD exists on a page or it does not. They do not measure coverage depth against the schema.org vocabulary. Boise Standard measures schema coverage as a percentage of the available vocabulary for a given entity type, scored against all 827 types and 1,528 properties. Most Treasure Valley businesses score under 30% coverage — meaning AI systems are still guessing about 70%+ of their most important properties. Schema.org launched in 2011 supporting three implementation formats. All three declare the same information. They differ in how they integrate with your HTML — and that difference determines how reliably machines can read them. Microdata embeds structured markup directly inside HTML tags using special attributes. The data layer and presentation layer share the same code. When your front-end code changes, your schema can break silently. Maintenance burden is high. RDFa — Resource Description Framework in Attributes — is the more expressive academic format, implemented through HTML attributes. More flexible than Microdata. More complex. Adoption has been declining since 2022. JSON-LD separates the structured data entirely from the visible HTML. Schema lives in a