Pricing

from $600.00 / 1,000 parsed fdds

FDD Item 19 Parser — Franchise AUV & Financial Performance

Search state franchise registries (Minnesota CARDS + Wisconsin DFI), download Franchise Disclosure Document PDFs, and extract Item 19 Financial Performance Representations — has-FPR flag, raw Item 19 text, every dollar figure, and best-effort average/median/high/low unit volume. No logins.

Pricing

from $600.00 / 1,000 parsed fdds

Rating

0.0

(0)

Developer

Esteban Ortega

Actor stats

Bookmarked

Total users

Monthly active users

4 hours ago

Last modified

Categories

Lead generation

Automation

You can access the FDD Item 19 Parser — Franchise AUV & Financial Performance programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.

Python

JavaScript

CLI

OpenAPI

HTTP

MCP

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          "franchiseNames": {
            "title": "Franchise names",
            "type": "array",
            "description": "One or more franchise or franchisor names to search for in the Minnesota CARDS registry (e.g. 'Jersey Mike's', 'Anytime Fitness'). Each name normally produces ONE record: the newest full FDD is downloaded and its Item 19 section parsed. CARDS matches franchise names by SUBSTRING, so a short string can match several franchisors. No document is billed twice in a run: repeated or whitespace-variant entries are collapsed before searching, and if two different names resolve to the same document it is delivered (and charged) once, with an unbilled log note naming the record that covers the other name. A name that returns nothing, that matches only non-FDD paperwork, or that is never reached because the maxFdds budget ran out also produces an unbilled log note, so no requested name ever disappears without explanation. Leave empty to use sweep mode (year + document type). You are billed per record returned, so maxFdds caps the cost.",
            "items": {
              "type": "string"
            }
          },
          "year": {
            "title": "Filing year (sweep mode)",
            "type": "string",
            "description": "Sweep mode: pull a batch of FDDs filed in this year (e.g. '2026') instead of by name. Combine with documentType to narrow (e.g. all 'Clean FDD' filed in 2026). When combined with franchiseNames, restricts each name's results to that filing year. Sweep mode downloads only genuine full FDD document types; if a sweep matches rows but none of them is an FDD, nothing is downloaded or billed and an unbilled diagnostic explains why."
          },
          "documentType": {
            "title": "Document type",
            "enum": [
              "",
              "Clean FDD",
              "Final FDD",
              "Marked FDD",
              "Revised FDD - Clean"
            ],
            "type": "string",
            "description": "Restrict to a Minnesota CARDS document type. 'Clean FDD' (the default when unset) is the standard full disclosure document and the best choice for Item 19 extraction. Choose 'Any document type' to apply no filter — the actor still downloads only full FDD document types (Clean, Final, Revised or Marked FDD) and never bills an amendment, consent or deficiency notice as an FDD. Applies to both name search and sweep mode.",
            "default": "Clean FDD"
          },
          "states": {
            "title": "States",
            "type": "array",
            "description": "Which state franchise registry to query. Minnesota CARDS is the source in this version: it offers full search, complete filing history, year sweeps and stable per-document PDF URLs, and because an FDD is a single national document most franchisors' disclosure documents are available there. 'MN' is the only supported value; support for a second registry (Wisconsin DFI) is planned for a later version. California and NASAA EFD are intentionally excluded because they block automated HTTP access.",
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                "MN"
              ],
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              ]
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              "MN"
            ]
          },
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            "maximum": 200,
            "type": "integer",
            "description": "Hard cap on the number of FDD PDFs downloaded and parsed per run — a single global budget across all names. One downloaded PDF produces exactly one dataset record, so each parsed FDD is one billed result and this cap is also your hard cost cap. No document is downloaded or billed twice in a run (Minnesota documents are deduplicated by CARDS document id across every name you request). Failed searches/downloads are never written to the dataset (they are reported in the run log and status message) and do NOT consume it either. If the budget runs out before every requested name is searched, each unsearched name is named in the run log with the value to raise this to. FDDs are large (5-7 MB, 400-500 pages) and PDF text extraction is CPU-bound, so budget roughly 20-40 seconds per FDD at the default 4 GB memory. The default of 3 keeps a first run quick; raise it (up to 200) for batch sweeps and raise the run timeout to match.",
            "default": 3
          },
          "downloadPdfToKvs": {
            "title": "Save FDD PDFs to key-value store",
            "type": "boolean",
            "description": "Also store each downloaded FDD PDF in the run's default key-value store (key returned as pdf_bytes_kvs_key). Turn on if you want the raw PDF, not just the extracted Item 19 fields. Adds storage but does not change per-result billing.",
            "default": false
          },
          "requestDelaySeconds": {
            "title": "Delay between requests (seconds)",
            "minimum": 0,
            "maximum": 10,
            "type": "integer",
            "description": "Politeness delay between HTTP requests to Minnesota CARDS. These are public government records with no published rate limit; 1-2 seconds is courteous. Lower values run faster but are less polite.",
            "default": 2
          },
          "proxyConfiguration": {
            "title": "Proxy configuration",
            "type": "object",
            "description": "Proxies for the HTTP requests. Minnesota CARDS is a public state-government site, so Apify Proxy (datacenter) is sufficient. Leave default unless the source rate-limits your IP.",
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              "useApifyProxy": true
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FDD Item 19 Parser - Franchise AUV & Revenue OpenAPI definition

OpenAPI is a standard for designing and describing RESTful APIs, allowing developers to define API structure, endpoints, and data formats in a machine-readable way. It simplifies API development, integration, and documentation.

OpenAPI is effective when used with AI agents and GPTs by standardizing how these systems interact with various APIs, for reliable integrations and efficient communication.

By defining machine-readable API specifications, OpenAPI allows AI models like GPTs to understand and use varied data sources, improving accuracy. This accelerates development, reduces errors, and provides context-aware responses, making OpenAPI a core component for AI applications.

You can download the OpenAPI definitions for FDD Item 19 Parser — Franchise AUV & Financial Performance from the options below:

OpenAPI.json

If you’d like to learn more about how OpenAPI powers GPTs, read our blog post.

You can also check out our other API clients:

FDD Item 19 Parser — Franchise AUV & Financial Performance API in Python

FDD Item 19 Parser — Franchise AUV & Financial Performance API in JavaScript

FDD Item 19 Parser — Franchise AUV & Financial Performance API through CLI

FDD Item 19 Parser — Franchise AUV & Financial Performance API

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