Every check, loan file, email, web chat, call, fax, statement and ID that crosses your network is read, classified, extracted and indexed the moment it arrives. FullText turns that traffic into one governed body of text, so your AI can answer any question from all of it.
Once everything is text, your AI can finally use all of it. Ask by voice or by typing. FullText retrieves every relevant check, loan document, email, chat, call and image, hands them to your model as cited context, and the answer comes back with its sources attached.
Checks, loan files, emails, web chats, calls, faxes and photos arrive faster than any team can read them, and none of it reaches your models in its raw form. FullText converts that flow, and the decades of backlog behind it, into a governed text layer your search, analytics, automation and AI can act on.
Ingest millions of pages and hours of media: paper, microfilm, image-only PDFs, fax, photos and video. Convert them to machine-readable text in batch or in real time.
Pull parties, dates, amounts, parcels, clauses and codes into structured records mapped to the systems you already run.
Full-text and semantic search across every archive and every tier, with answers that cite the exact book, page and line.
Confidence scoring, human review and complete provenance, so AI acts on verified information instead of guesses.
Recognition is only half the job. FullText runs as a secure, multi-tenant platform that keeps sensitive data isolated, compliant and affordable to store for as long as the law requires.
The text index and metadata catalog stay hot, while the source images move to the lowest-cost tier your policy allows. Your teams query decades of records instantly and only retrieve the original page when they need it.
Pixels are for eyes. Text is for machines. Every search index, every model and every agent reasons in words. Anything that hasn't been converted to text, whether scanned, handwritten, photographed or spoken, is invisible to them. That gap is where FullText works.
If a record can't be read, it can't be indexed, searched, or cited.
AI is only as reliable as the text beneath it. Every word needs a confidence score and a verifiable source.
Before analytics, before answers, before agents, something has to read the page. That is the layer we own.
Any source a person can see or hear enters on the left. Out the right comes enterprise-grade text: structured, indexed, governed and traceable to the exact pixel it came from.
Documents are only the start. FullText describes what is in a photo, transcribes what is said in a recording and indexes both next to your records, so one search finds the page, the frame and the second.
Point FullText at cloud drives, document systems, S3 buckets, email and scanners.
Every file is read, described, transcribed, classified and indexed automatically.
Search in plain language. Every answer cites the page, frame or second it came from.
Computer vision finds every object, reads every sign and number in the frame, measures what it sees, and writes a description your search engine and your AI can use.
Single-story frame house with a blue tarp over storm damage on the rear roof slope. An oak limb overhangs the roof. "For Sale" sign in the front yard, pickup truck in the driveway.
GPS 28.0395, −81.9498 → 1420 Orange Ave → parcel NE¼ SW¼ 14-28-24
FullText scans overhead imagery for every class you care about, counts and measures each one, and writes the scene down as text that can be searched next to the claim, the permit and the deed.
Home A 152 m² · Home B 114 m² · barn 308 m²
3 cars, 1 box truck · 2 parked on site, 2 on road
By the pool, at the barn door and at the paddock gate
All inside the paddock · paddock area 0.42 ha
Home B · blue tarp ≈ 38 m² · confidence 0.94
Rural residential parcel of 1.86 ha. Two single-family homes and one metal-roof barn. Home B shows a blue tarp over roughly 38 m² of roof, consistent with storm damage. Four vehicles: three passenger cars and one box truck. Five horses inside a 0.42 ha paddock east of the barn. Three people on site. Pool behind Home A.
Speech is transcribed with speaker labels and timestamps. Dates, places and claims are pulled out, and anything that conflicts with the record is flagged for review.
Claimant says the roof was replaced in 2019 00:27. The most recent roof permit on file was issued in 2009 Permit B09-1187.
Roof tarp detected · mailbox reads "1420" · 2026-09-14
"1420 Orange Avenue. We put a tarp on it the next morning."
Re-roof, 1420 Orange Ave, issued 2009
NE¼ SW¼ Sec. 14-28-24, easement 15 ft along the east line
Full text means every word of every file is indexed, including the words inside images, faxes and calls. On top of that index, FullText reads a question the way a person asks it, then turns it into a precise search with filters, synonyms, misspellings, sound-alike names, proximity and ranges. You see exactly what it ran and why each result matched.
"late fee"Words in that exact order.
roof NEAR/5 tarpWords within five words of each other, in any order.
Halverson~Finds Halvorsen, Halvorson and OCR slips like Ha1vorsen.
sounds:"Kathryn"Matches Catherine and Katharine in transcripts and handwriting.
replace*replaced, replacement, re-roof, new roof.
amount:>40000Amounts, dates, sizes and confidence scores.
said: · shows: · reads:Search what was spoken, what is pictured and what is written.
NOT team:treasuryLeave out senders, sources, folders or document types.
One platform unifies computer vision, OCR, handwriting recognition, extraction and AI search. Deploy a single stage or run the full pipeline and close the gap between what your organization holds and what its AI can use.
Understands document structure before reading a word: tables, stamps, signatures, seals, margins and the regions that carry meaning. In video, it finds the frames and events worth describing.
Printed type, cursive, typewriter carbons, faded microfilm, noisy fax and recorded speech, each recognized with a confidence score on every character.
Converts pages into system-ready records (parties, dates, amounts, parcels, clauses and codes) mapped to the schemas you already use, and catalogs the metadata for retrieval.
Exact-phrase precision when you know the words, semantic recall when you don't. Search spans hot, warm and archived content, and every result opens on the highlighted source.
Query millions of pages in plain language. Answers are grounded in, and cited to, the book, page and line they came from, ready to feed agents and analytics.
Every word retains its coordinates, page and confidence, with a full audit trail. Low-confidence text routes to human review and never slips silently into your model.
The proof point for "everything becomes text" is the record that was never meant for a computer: the handwritten deed book at the county courthouse.
Every parcel has a paper trail — deeds, mortgages, liens, easements, plats, surveys and notary acknowledgments. Much of it lives in handwritten ledgers, typewriter carbons, microfilm reels and image-only scans that no search box can see.
So title work is still done by eye: an examiner paging book by book to prove a chain of ownership. FullText reads all of it, every hand, every era and every format, and turns a county's history into one searchable, citable record that title, lending and insurance teams can act on in minutes.
grantor: Calloway
easement: 15 ft Elender: First Fed.
ref: DB 312/44releases: OR 88/210
status: satisfiedgrantee: utility co.
width: 10 ftsetback_E: 1.2 ft
flag: encroachmentA pixel is a square of light. A voxel is a cube of space. FullVoxel takes LiDAR, drone photogrammetry, CT and building scans and writes them down as text an AI can search: what's there, how big it is, and what it's too close to.
Managed service providers, records-management firms and systems integrators can run FullText as a shared, multi-tenant platform and sell recognition, search and retention as recurring services.
Turn storage and scanning contracts into higher-margin AI data services with per-tenant metering and billing.
Once a client's archive is searchable through you, it becomes part of how they work every day.
Built-in isolation, encryption and audit trails let you serve healthcare, finance, legal and public-sector clients with confidence.
Continuous ingestion, instant search, AI answers and dedicated review queues.
Scheduled batch recognition with full search and extraction.
Low-cost retention with a searchable index over cold storage.
Send a file, a folder, a bucket or a live stream. Receive text, fields, coordinates and confidence scores, ready for your search index, your systems of record or your model's context window.
# Read a 1923 quitclaim deed and pull the fields that matter curl https://api.fulltext.ai/v1/read \ -F file=@deed_book_312_p44.tif \ -F schema=land_record # → { "text": "THIS QUITCLAIM DEED, executed this 14th day of March…", "fields": { "type": "quitclaim_deed", "date": "1923-03-14", "grantor": "Josiah P. Calloway", "parcel": "NE1/4 SW1/4 S14 T28S R24E", "easements": [{ "width_ft": 15, "side": "east" }] }, "provenance": { "page": 44, "line": 7, "bbox": [212,88,604,112], "confidence": 0.97 } }
Faded, handwritten, scanned sideways or simply too large to read by hand. Tell us what's locked in your archive and we'll run a pilot that shows exactly what FullText can extract from it.