Search newspapers, city directories and permits at once, in plain language, and cite every fact straight to its source page.
Historic tax-credit applications and federal Section 106 reviews both require a documented history: owners, uses, fires, alterations. It's assembled by hand from newspapers, city directories and permits, for every project.
Every newspaper mention of the Grand Hotel, 1900 to 1950
Who occupied 212 Front Street in each decade?
Fires, demolitions or alterations recorded for this block
Load scans of local newspapers, city directories and permits for the building or district you're documenting.
AI reads old print and handwriting in any language, and flags pages it can't make out rather than guessing at them.
Records are indexed by meaning, with owners, occupants, uses and dates captured across decades.
Ask for a building's or block's history in plain language and get a cited answer, ready for the application or report.
Timelines and entity maps built from your loaded records
Every fact cited to its page, ready for the application or report
Search across directories, newspapers and permits at once
Handles old print and handwriting in any language
Each account's documents sit in an isolated database and storage bucket, enforced by row-level security — no other customer can see or search them.
Encrypted in transit (TLS 1.2+) and encrypted at rest.
Your documents are never used to train AI models — we instruct our providers not to train on your data.
Documents are stored in the United States.
Deleted on request, and removed within 30 days of an account closing.
A published list of every subprocessor that touches your data, with its role and location (legal.archivelm.com/legal/subprocessors on the main site).
We are not yet SOC 2 certified. We'll share our security overview and subprocessor list on request.
| Plan | What's included | Price |
|---|---|---|
| Try it | ||
| Explorer (Free) | 25 credits/month — enough to load your own hardest pages and see what it finds | $0 |
| Plans | ||
| Researcher | Individual plan — 100 credits/month, semantic search, AI Librarian chat, Research Lab, unlimited exports | $15/mo |
| Team | Up to 5 seats — 420 credits/month, all research features | $49/mo |
| Department | Up to 15 seats — 2500 credits/month, priority support | $249/mo |
| Large backlogs | ||
| Project pricing | A one-off bulk digitization project for a large backlog, priced per page instead of by plan | from 6¢/page at volume |
A dense newspaper page uses more credits than a book or letter page, because it takes more work to read. Ask us which plan fits your backlog before you commit.
You bring the documents — newspapers, city directories, permits and other local records you already hold or can obtain. ArchiveLM doesn't supply source records; it reads, indexes, and makes searchable what you load into your own account.
It's flagged, not guessed. Historical scans degrade, fade, and get handwritten over — when confidence is too low to trust, the page is marked for review instead of silently producing a confident-looking answer that isn't on the page.
Yes. Semantic search works across languages — an English query can surface a foreign-language record for an immigrant-owned business or congregation by meaning, not just keyword match, and the AI Librarian can answer in English while citing the source-language passage it relied on.
Row-level security isolates every account's documents in their own database rows and storage bucket. No other customer can see or search your collection, and nothing you upload is used to train AI models.
The free tier includes 25 credits a month, enough to load a handful of your hardest pages and see exactly what it finds and where it fails. Paid plans start at $15/month; large one-off backlogs are priced per page instead.
Research Lab's Timeline and Entity Map tools generate a chronological and name-indexed view across whatever records you select, drawn only from the text extracted from your documents — useful as a draft to verify, not a substitute for citing the underlying page.
Send up to 50 pages of your own records for a building or district you're documenting. We'll run them and show you exactly what ArchiveLM finds, and where it can't read a page.
ArchiveLM is in private beta. We review each request and typically respond within 1–3 business days.