# Self-Indexing EagleWeb → Searchable Index: Design, Feasibility & Legal Notes **Question posed by owner:** *If we pull ALL recordings from EagleWeb (not just my parcels) into an Azure AI Search index, can we then find the malicious / wild deed? And since my title was cleared 3 years ago, the bad filing must be after that — right? And if a recording was denied, does that stop me from selling?* This note is technical + general information only. **It is not legal advice.** Confirm the legal points with your attorney and title company (Chicago Title). --- ## 1. Does an Azure AI Search index help? YES — it removes EagleWeb's core limitation. EagleWeb's **public** search only lets you query the county's *index fields*: grantor/grantee **name**, **parcel**, **PLSS section**, **book/page**, **doc number**, **date/type**. It cannot search the **content** of the scanned document images, and it cannot search by **geography** (where the described land actually is). A wild deed hides precisely in those blind spots: - filed under a **fabricated grantor name** you'd never think to search, and/or - carrying a **legal description that the recorder never tied to your parcel numbers** (so a name/parcel search misses it), and/or - **rejected / pending** — never published to EagleWeb at all (see §5). An Azure AI Search index built from the document **images + OCR text** converts the problem from "search the county's name index" into "search the actual words and the geography of every instrument." That is effectively a **do-it-yourself title plant** — the same concept Chicago Title uses. This is a genuinely good fit for Azure AI Search because it has a built-in **OCR / AI-enrichment skillset** (Azure AI Document Intelligence / Vision Read) that turns the scanned PDFs into searchable text automatically. ## 2. Proposed architecture (bounded, tractable) ``` EagleWeb (Tyler EagleRecorder) │ (1) Acquisition: scrape the recording INDEX (metadata) for a bounded date window, │ then download each document IMAGE (PDF) via viewAttachment.jsp ▼ Blob storage (raw PDFs + a metadata JSON per doc) │ (2) Enrichment: OCR each PDF → full text (Azure AI Search skillset, or Doc Intelligence) │ + entity/keyphrase extraction; parse legal-description calls ▼ Azure AI Search index (fields below) │ (3) Research: full-text + semantic queries; grantor≠owner flags; geo/legal matching ▼ Hit list → manual review → pull certified copies of anything probative ``` ### Suggested index schema (one document = one recorded instrument) | Field | Type | Source | |-------|------|--------| | docNumber | Edm.String (key) | index | | docType | String, facetable | index | | recDate | DateTimeOffset, sortable/filterable | index | | grantor / grantee | Collection(String), searchable | index | | bookPage | String | index | | parcelIds | Collection(String), filterable | index (may be empty ← the whole point) | | plssSection/Township/Range | String, filterable | index | | legalDescriptionText | String, searchable | OCR | | fullText | String, searchable (analyzer=standard) | OCR | | addressesMentioned | Collection(String) | enrichment | | namesMentioned | Collection(String) | enrichment | | geoParsedFootprint | Edm.GeographyPolygon (optional) | metes-and-bounds parse | | blobUrl | String | acquisition | ### Detection queries (once indexed) 1. **Content match on the subjects** — search `fullText`/`legalDescriptionText` for: `4927 Katya`, `4924 Katya`, `R32905-401-5010`, `R32905-400-4740`, `SP 79-192`, `383-4650`, distinctive metes calls (`N5*W423`, `S89*E843`), and owner names **incl. misspellings** (Rutter/Ruter/Rutten, Garibyan/Garabyan/Garibian). A hit that is **NOT** already indexed to your parcels = prime suspect. 2. **Grantor ≠ record owner** — join every conveyance's grantor against the verified true-owner table (`03_assessor/owners_and_deeds.csv`). A stranger-to-title grantor on/near your land is the classic wild-deed signature. (A parcel-scoped version already run: `WILD_DEED_heuristics.txt`.) 3. **Geography** — if legals are geo-parsed, spatially intersect every instrument's footprint with your two parcels regardless of how it was indexed. This catches the "mis-tied legal" case that the public index structurally cannot. ## 3. Scope it by DATE — the owner's key insight (mostly correct) Because a competent title search + owner's policy was issued at your **2023 purchase** (Rutter WD **#4565727**, from Bloom), the recorded chain was clean **as of that date**. So a **newly recorded** malicious deed most likely lands in the window **2023-06 (your closing) → present**, with the neighbor's map (dated ~2026) suggesting it is recent. That bounds a county-wide pull to ~3 years instead of "all of time," which makes this **very tractable** (low thousands of instruments, not hundreds of thousands). **Caveats to the "must be after closing" assumption:** - A wild deed could *predate* closing yet have been **mis-indexed** so the 2023 title search missed it. But a properly *recorded* deed affecting your parcel should have surfaced in a plant search — and if a covered defect predates your policy, **your owner's title policy is the remedy** (the title company must defend/clear it). So the *new-filing* search window is post-closing, while *pre-closing* defects are a title-insurance claim, not a search project. - The **Garibyan** parcel took title differently (Decree of Dissolution **#4383543**), so its clean- date baseline differs. Confirm each parcel's policy/effective date with the title company. - **Action:** ask Chicago Title for the **effective date** of your owner's policy and a current **date-down / title commitment** — that tells you what is of record *right now* vs. at closing. ## 4. Cost / effort / risk of the pull - **Volume:** date-bounded county-wide (2023→present, all doc types) is plausibly a few thousand docs → OCR cost is modest (Azure Doc Intelligence Read ~ per-page pricing). "All recordings ever" is *not* recommended — large, costly, and unnecessary given §3. - **Terms of use / rate limits:** EagleWeb is a public portal but bulk scraping may hit rate limits or ToS restrictions. Throttle, identify politely, and prefer the **narrowest date window** that brackets the suspected filing. The Auditor can also provide a **bulk data / land-index extract** directly — often the cleaner, sanctioned route than scraping. - **OCR quality:** old typewritten/handwritten metes-and-bounds OCR imperfectly; geo-parsing is best-effort. Treat hits as leads, then pull **certified copies**. ## 5. "If a recording was DENIED, can I still sell?" (general info — confirm with attorney) - A **rejected / denied** filing is **not entered into the official record**. Under WA recording law, an instrument that is not recorded gives **no constructive notice** and generally has **no effect on your title**. **By itself, a rejected filing does not cloud title and should not prevent a sale.** It also will **not** appear in EagleWeb — which is exactly why "download everything" cannot find a rejected filing (§1). - **But** watch the practical risks: - the filer can **re-submit** a corrected version, or record a **different** instrument that *is* accepted (that **would** cloud title until removed); - they could file a **lawsuit / lis pendens**, which clouds title even if meritless; - during escrow, a title company may still **flag** a known fraud attempt and require extra proof, slowing (not blocking) a sale; - WA law provides remedies for fraudulent filings (e.g., quiet-title and slander-of-title actions, and criminal statutes for filing false instruments) — your attorney can pursue these. - **Net:** a purely rejected filing = no legal cloud, sale not blocked, but **document it and monitor** the recorder for re-attempts. Ask the Auditor whether they retain a **rejected/pending queue** and whether your name/legal is in it. ## 6. Bottom line - Azure AI Search is a sound backend; the **hard part is acquisition + OCR**, which is identical regardless of index engine. For a corpus this small, a local full-text index (e.g., SQLite FTS5) would also work, but Azure AI Search's built-in OCR skillset + semantic search is the least-effort path if an Azure subscription is available. - **Highest-value scope:** county-wide, **all doc types**, **date-bounded 2023→present**, indexed by **content + geography**, with a **grantor≠true-owner** flag. This is ~90% of the benefit of "index everything" at a fraction of the cost/risk. - It still **cannot** find a **rejected/pending** filing — for that, the only sources are Chicago Title's plant (they made the 2026 map; they likely have the instrument #) and the Auditor's counter (request a land/legal-description search **and** a check of the pending/rejected queue).