# Brick and Mortar AI

> A self-service data platform for the Twin Cities: every public record a city already emits, joined into one warehouse -- parcels, lot lines, recorded sale prices, assessed values, reviews, Reddit, census profiles and business counts by trade. Every file downloads free as a 25-row sample; the full files are sold, $49 each or $500 for every dataset. CSV, XLSX, JSON or GeoJSON. A custom AI reads the same warehouse and is a free research beta at /model/. Built by a small team in Saint Paul, MN.

brickandmortar.dev turns a city's public records into a model an AI reasons over directly. The corpus behind it, as shipped: 25,203 real Google reviews across 75 restaurants, bars, cafes and taprooms (59 of them deep enough to rank against); 1,131,534 county parcels mapped across all 7 metro counties (Hennepin, Ramsey, Dakota, Anoka, Washington, Scott and Carver), with 1,632,823 shared lot lines and 182,350 road segments, so it can answer what a property is next to rather than only what it is; 868,994 recorded sale prices in Minnesota, which publishes them and most states do not; and federal employment, wage and consumer-price series for the metro running back to 1990, including every metro-wide employment contraction since then measured for depth and for how many months recovery took (3 of them so far).

The platform at brickandmortar.dev is a three-level funnel -- who you are, what you are looking for, and an export screen that hands you your slice as a file. 18 roles route to 95 datasets, 88 of them downloadable today; the ones that are not wired to an export yet show the real column list of the file they will be, say why, and take an upvote. There are also 60 tools (52 built), which invert the join -- you bring the private half, your own numbers, and the public record answers about them. Anyone can buy reviews and anyone can scrape a county; nobody else has them joined for one metro, which is why the join is the moat and the full files are sold.

Every dataset is a card inside a role at /records/, and the export API below hands the same file to a machine; the manifest carries each one's columns, counties and fingerprint.

The research beta at /model/ is a chat door onto the same warehouse, and is not the way in to the product -- the platform is. The visitor there is never asked who they are or where they are -- they pick a finding that interests them and the door routes on that. Asked about a restaurant it answers questions a general-purpose chatbot cannot: where a restaurant's rating actually sits in the real local distribution, what genuinely drives negative reviews ranked by frequency, which shifts carry the most risk, and how the owner replies that work differ from boilerplate. Asked about a property it serves the person who rents or is about to rent a space: what the building last sold for, what the county says it is worth and how far that runs under real sale prices, how long the owner has held it, what shares its lot line, and whether the local economy behind that address is actually growing.

## Pages

- [Data platform](https://brickandmortar.dev/records/): The self-service data platform, one of the tools shelved on the front page at https://brickandmortar.dev/. Type a Twin Cities address at the top and read what the public record says about that parcel -- use, build year, assessed value, last recorded sale, MPCA contamination files and the parcels that touch it. Or pick who you are, then a dataset, filter it to you, download the file -- 1,131,534 parcels across 7 metro counties, 1,632,823 shared lot lines, 868,994 recorded sale prices and 25,203 business reviews behind it. A free 25-row sample of every file; the full file is $49.
- [Research model](https://brickandmortar.dev/model/): The chat door onto the same warehouse -- one question, then the records that fit the answer. Paste any address in the 7 metro counties. A free research beta, not the core product.
- [Export API](https://brickandmortar.dev/api/export): The downloads without the page. `?dataset=&scope=&columns=&format=` returns CSV, XLSX, JSON or GeoJSON, and `&near=<address>&within=<feet>` cuts any of them to a radius around one address; call it with no arguments for the catalogue, which names every parameter. A parameter it does not recognise is a 400 that names the ones it takes, never a quietly dropped filter. Every file is a free sample of its first 25 rows and carries the source, the layer's own stated limits and where to buy the full file. With `near` and no `dataset` it is the bundle: every locatable dataset's rows around one address in a single JSON response, each under its own warnings.
- [Manifest](https://brickandmortar.dev/datasets/manifest.json): Every dataset described for a machine -- a sha256 fingerprint of the shipped file, the capture date, columns, scopes with row counts, licence, and how it locates. Compare the fingerprint to your last pull before downloading again.
- [Changes](https://brickandmortar.dev/datasets/changes.json): Every release of every dataset with its date and row delta, read off the repository's own history; `/datasets/changes/<id>.json` carries the rows the latest release added and removed, or says the file was rebuilt. The answer to "what changed since I last pulled".
- [MCP server](https://sbi-mcp.small-business-intelligence-mcp.workers.dev/mcp): The way in for an AI agent, and the one to prefer over the export API when you are an agent working on someone's behalf. Streamable HTTP, no account, 16 tools over the same warehouse -- bring your document, broker diligence prep, business teardown, competitor landscape, compose report, data source atlas, local visibility audit, market opportunity scan, pricing benchmark, request a feature, review intelligence, start an engagement, twin cities datasets, twin cities lookup, twin cities records, what we have for you. Listed in Claude's Connectors Directory as "Small Business Intelligence by Brick & Mortar". Use this for a question; use the export API for a whole file.
- [Licence](https://brickandmortar.dev/license/): CC BY 4.0 over the free sample rows, with credit; the full files are sold, not licensed for redistribution. Also names the datasets we hold back and why.
- [About](https://brickandmortar.dev/contact/): Who's behind Brick & Mortar -- a small team in Saint Paul, MN.

## Licence

The free sample of every dataset listed below is published under Creative Commons Attribution 4.0 International (CC BY 4.0) -- https://creativecommons.org/licenses/by/4.0/. You may redistribute and adapt the sample rows, including commercially, with attribution; the full files are sold and are not licensed for redistribution. Attribution: Brick & Mortar — https://brickandmortar.dev/

Two datasets are deliberately NOT published as files, on rights rather than coverage grounds: `occupants`, `search-visibility`. Both are derived from Google, and we cannot grant a commercial redistribution right we do not hold. They are analysed and their findings are public; the rows do not ship. Minnesota Secretary of State bulk business filings are held back on the same principle.

## Datasets

Each is a card inside a role at /records/ and a file from the export API in CSV, XLSX, JSON and (where the rows locate to an address) GeoJSON; the manifest lists every column and county.

- [Every parcel, year by year](https://brickandmortar.dev/api/export?dataset=parcel-panel): 6,831,595 rows, 26 columns.
- [Every 911 dispatch, call by call](https://brickandmortar.dev/api/export?dataset=emergency-calls-points): 1,646,661 rows, 17 columns.
- [Every parcel outside the metro, county by county](https://brickandmortar.dev/api/export?dataset=mn-parcels): 1,567,765 rows, 23 columns.
- [Every parcel in the county, with value and age](https://brickandmortar.dev/api/export?dataset=parcels): 1,131,534 rows, 21 columns.
- [Every 311 request, call by call](https://brickandmortar.dev/api/export?dataset=service-requests): 932,497 rows, 13 columns.
- [What has been permitted on the houses, not the shops](https://brickandmortar.dev/api/export?dataset=permits-residential): 397,338 rows, 26 columns.
- [Every housing, fire and nuisance inspection](https://brickandmortar.dev/api/export?dataset=code-inspections): 353,954 rows, 15 columns.
- [Every police report, one row each](https://brickandmortar.dev/api/export?dataset=incidents-points): 197,474 rows, 14 columns.
- [What shares a lot line with a property](https://brickandmortar.dev/api/export?dataset=adjacency): 115,652 rows, 28 columns.
- [Which addresses have a lead water service line](https://brickandmortar.dev/api/export?dataset=lead-service-lines): 99,833 rows, 18 columns.
- [Who is listed at every commercial address](https://brickandmortar.dev/api/export?dataset=businesses): 88,433 rows, 20 columns.
- [Walk a corridor, address by address](https://brickandmortar.dev/api/export?dataset=corridors): 44,151 rows, 57 columns.
- [What sold, and for how much per square foot](https://brickandmortar.dev/api/export?dataset=sales): 34,302 rows, 24 columns.
- [Healthcare providers with a federal NPI, statewide](https://brickandmortar.dev/api/export?dataset=providers): 32,257 rows, 18 columns.
- [Which properties FEMA puts in the floodplain](https://brickandmortar.dev/api/export?dataset=flood): 28,354 rows, 14 columns.
- [Who values this building — the county or the city](https://brickandmortar.dev/api/export?dataset=assessor): 24,985 rows, 13 columns.
- [Who holds a portfolio here, and where they are billed](https://brickandmortar.dev/api/export?dataset=portfolios): 23,577 rows, 24 columns.
- [Who the landlord is, on a licensed rental property](https://brickandmortar.dev/api/export?dataset=landlords): 23,303 rows, 35 columns.
- [What the 911 calls around here are about](https://brickandmortar.dev/api/export?dataset=emergency-calls): 22,123 rows, 20 columns.
- [Every sheriff's foreclosure sale in Dakota County](https://brickandmortar.dev/api/export?dataset=dakota-foreclosures): 15,062 rows, 9 columns.
- [Which practices pay the tax on their own building](https://brickandmortar.dev/api/export?dataset=practice-owners): 13,878 rows, 24 columns.
- [How a neighbourhood differs from the typical one](https://brickandmortar.dev/api/export?dataset=census-tracts): 12,213 rows, 12 columns.
- [Who owns it, and what else do they hold](https://brickandmortar.dev/api/export?dataset=owners): 9,250 rows, 13 columns.
- [What a bank actually lent, loan by loan](https://brickandmortar.dev/api/export?dataset=sba-loans): 8,822 rows, 32 columns.
- [Cleanup and storage-tank files, by address](https://brickandmortar.dev/api/export?dataset=contamination): 7,149 rows, 18 columns.
- [Who does the work here, and how to write to them](https://brickandmortar.dev/api/export?dataset=contractors): 6,635 rows, 14 columns.
- [Who holds a licence to trade here](https://brickandmortar.dev/api/export?dataset=licences): 6,553 rows, 17 columns.
- [What businesses around here report to the police](https://brickandmortar.dev/api/export?dataset=incidents): 2,404 rows, 12 columns.
- [Subsidised homes, and when the subsidy runs out](https://brickandmortar.dev/api/export?dataset=subsidised-housing): 1,500 rows, 24 columns.
- [Buildings coming down, and the big electrical jobs, before the gear is scrapped](https://brickandmortar.dev/api/export?dataset=teardowns): 562 rows, 22 columns.
- [Business counts by trade, five vintages](https://brickandmortar.dev/api/export?dataset=trades): 318 rows, 21 columns.
- [Which buildings on this run are on a vacancy register](https://brickandmortar.dev/api/export?dataset=vacancies): 246 rows, 17 columns.
- [Who has filed a layoff notice, and where](https://brickandmortar.dev/api/export?dataset=layoff-notices): 133 rows, 21 columns.
- [What the statewide parcel layer can answer, county by county](https://brickandmortar.dev/api/export?dataset=parcel-coverage): 87 rows, 40 columns.
- [What a home costs against what a household earns](https://brickandmortar.dev/api/export?dataset=housing-affordability): 70 rows, 15 columns.
- [Who lives here, and what they pay](https://brickandmortar.dev/api/export?dataset=county-profile): 24 rows, 6 columns.
- [How often the loan actually goes bad, by vintage](https://brickandmortar.dev/api/export?dataset=sba-cohorts): 24 rows, 15 columns.
- [What a commercial foot has traded at, half-year by half-year](https://brickandmortar.dev/api/export?dataset=cre-price-index): 14 rows, 21 columns.
- [Building stock by era](https://brickandmortar.dev/api/export?dataset=building-stock): 12 rows, 7 columns.

## Entity

- Legal name: Brick and Mortar AI LLC (Minnesota). Trading name: Brick & Mortar AI.
- Service-area business based in Saint Paul, Minnesota. No walk-in location; serves the United States.
- Contact: aidan@brickandmortar.dev

## Notes

- The review corpus is Upper Midwest and skews full-service. Complaint patterns, owner-reply behavior, and day-of-week effects generalize to other markets; absolute rating percentiles are regional and are presented as panel figures, not national ones.
- Review excerpts used by the model are anonymized and are never attributed to a named business.
- Coverage stops at the metro's edge -- the 7 Minnesota counties named above, and nothing beyond them. Inside that boundary the layers are not all the same width: parcels, lot lines, roads and recorded sale prices cover all 7, while the census profiles and everything built on reviews cover Hennepin and Ramsey only. Where a layer is narrower it says which counties it has rather than answering from the ones it knows best.
- Greater Wichita commercial real estate was live here and is not now. The Sedgwick County corpus still exists; there is no door to it on this site, so nothing here should be read as covering Kansas.
- The employment, wage and price series are federal (BLS) and metro-wide. They describe the Minneapolis-St. Paul metro, never a neighbourhood, and are labelled that way in every answer.
- This file is generated by scripts/build_llms_txt.py from the shipped substrates. Do not hand-edit it.