Data products · APIs

Primary-source records,
made machine-readable.

Remulous Labs normalizes messy public records — H-1B certifications, WARN Act layoffs, FBI crime statistics — into clean, provenance-linked APIs. One documented endpoint per dataset, instead of dozens of scattered portals and files.

3live APIs
728k+records indexed
17,000+cities covered
29 + DCstates of WARN coverage

Start in three steps

No sales calls. No setup. Get live provenance-cited data in under five minutes.

1

Pick an API below

Browse the three APIs and choose the dataset that fits your use case. Each is independent — use one or all three.

2

Subscribe on RapidAPI

Free tier included on every product. No credit card required to start. Upgrade when you need more monthly calls.

3

Make your first call

Swap your key into the snippet below, hit the endpoint, and you're reading live data with provenance on every record.

curl -X GET "https://sponsorlens-h-1b-labor-cert-api.p.rapidapi.com/v1/certifications?employer=nvidia&program=h-1b&limit=5" \
  -H "X-RapidAPI-Key: YOUR_KEY_HERE" \
  -H "X-RapidAPI-Host: sponsorlens-h-1b-labor-cert-api.p.rapidapi.com"

Example using SponsorLens. Replace employer=nvidia with any employer, or filter by program (h-1b, perm, h-2a, h-2b). → Get your key on RapidAPI

One account. Three US public-records APIs.

Each is independent — use one or all three. Same free tier, same schema conventions, same provenance model across every product.

Labor

LayoffLens

Provenance-first state WARN-notice layoffs data — real notices, normalized across states, each traceable back to its official source filing.

29 states + DC Daily refresh 2024–present
GET /v1/notices

Built for: HR tech · financial analysis · journalism

Docs & pricing
Public safety

UCRLens

FBI UCR crime statistics for 17,000+ US cities and all 50 states — 8 Part I offenses with per-100k rates and 8-year trends. Parsed from the official RETA master file.

17,000+ cities All 50 states 2018–2025
GET /v1/crime/city

Built for: location intelligence · proptech · civic data

Docs & pricing

Request & response

Records carry source provenance where available — agency, source URL, and ingestion timestamp.

Request

curl -X GET "https://sponsorlens-h-1b-labor-cert-api.p.rapidapi.com/v1/certifications?employer=nvidia&program=h-1b&limit=1" \
  -H "X-RapidAPI-Key: YOUR_KEY_HERE" \
  -H "X-RapidAPI-Host: sponsorlens-h-1b-labor-cert-api.p.rapidapi.com"
const url =
  "https://sponsorlens-h-1b-labor-cert-api.p.rapidapi.com/v1/certifications?employer=nvidia&program=h-1b&limit=1";
const res = await fetch(url, {
  headers: {
    "X-RapidAPI-Key": "YOUR_KEY_HERE",
    "X-RapidAPI-Host": "sponsorlens-h-1b-labor-cert-api.p.rapidapi.com"
  }
});
const data = await res.json();
console.log(data.certifications);
import requests

url = "https://sponsorlens-h-1b-labor-cert-api.p.rapidapi.com/v1/certifications"
headers = {
    "X-RapidAPI-Key": "YOUR_KEY_HERE",
    "X-RapidAPI-Host": "sponsorlens-h-1b-labor-cert-api.p.rapidapi.com",
}
params = {"employer": "nvidia", "program": "h-1b", "limit": 1}
data = requests.get(url, headers=headers, params=params).json()
print(data["certifications"])

Response

{
  "count": 1190,
  "limit": 1,
  "offset": 0,
  "filters": { "employer": "nvidia", "program": "h-1b" },
  "certifications": [
    {
      "id": "0e18043133d39b7b",
      "employer": "NVIDIA Corporation",
      "ticker": "NVDA",
      "program": "h-1b",
      "case_status": "certified",
      "job_title": "Software Engineer",
      "soc_code": "15-1252.00",
      "soc_title": "Software Developers",
      "worksite_city": "Redmond",
      "worksite_state": "WA",
      "wage": { "from": 212202.0, "to": 235750.0, "unit": "year",
               "annual_from": 212202.0, "annual_to": 235750.0 },
      "prevailing_wage": { "amount": 212202.0, "unit": "year", "annual": 212202.0 },
      "decision_date": "2025-12-30",
      "fiscal_year": 2026,
      "provenance": {
        "source": "DOL-OFLC-LCA",
        "source_url": "https://www.dol.gov/.../LCA_Disclosure_Data_FY2026_Q1.xlsx",
        "ingested_at": "2026-06-11T23:43:14+00:00"
      }
    }
  ]
}

Request

curl -X GET "https://layofflens-warn-data-api.p.rapidapi.com/v1/notices?state=TX&min_affected=100&limit=2" \
  -H "X-RapidAPI-Key: YOUR_KEY_HERE" \
  -H "X-RapidAPI-Host: layofflens-warn-data-api.p.rapidapi.com"
const url =
  "https://layofflens-warn-data-api.p.rapidapi.com/v1/notices?state=TX&min_affected=100&limit=2";
const res = await fetch(url, {
  headers: {
    "X-RapidAPI-Key": "YOUR_KEY_HERE",
    "X-RapidAPI-Host": "layofflens-warn-data-api.p.rapidapi.com"
  }
});
const data = await res.json();
console.log(data.notices);
import requests

url = "https://layofflens-warn-data-api.p.rapidapi.com/v1/notices"
headers = {
    "X-RapidAPI-Key": "YOUR_KEY_HERE",
    "X-RapidAPI-Host": "layofflens-warn-data-api.p.rapidapi.com",
}
params = {"state": "TX", "min_affected": 100, "limit": 2}
data = requests.get(url, headers=headers, params=params).json()
print(data["notices"])

Response

{
  "count": 117,
  "limit": 2,
  "offset": 0,
  "filters": { "state": "TX", "min_affected": 100 },
  "notices": [
    {
      "id": "58fd002ecfef07bf",
      "employer": "JPMorgan Chase & Co.",
      "state": "TX",
      "city": "Plano",
      "county": "Collin",
      "num_affected": 244,
      "notice_date": "2026-06-23",
      "effective_date": "2026-08-21",
      "provenance": {
        "source": "TX-TWC",
        "source_url": "https://www.twc.texas.gov/.../warn-act-listings-2026-twc.xlsx",
        "ingested_at": "2026-07-04T07:27:02+00:00",
        "filing_lag_days": 59
      }
    }
  ]
}

Request

curl -X GET "https://us-city-crime-statistics-fbi-ucr17.p.rapidapi.com/v1/crime/city?city=Dayton&state=OH&year=2024" \
  -H "X-RapidAPI-Key: YOUR_KEY_HERE" \
  -H "X-RapidAPI-Host: us-city-crime-statistics-fbi-ucr17.p.rapidapi.com"
const url =
  "https://us-city-crime-statistics-fbi-ucr17.p.rapidapi.com/v1/crime/city?city=Dayton&state=OH&year=2024";
const res = await fetch(url, {
  headers: {
    "X-RapidAPI-Key": "YOUR_KEY_HERE",
    "X-RapidAPI-Host": "us-city-crime-statistics-fbi-ucr17.p.rapidapi.com"
  }
});
const data = await res.json();
console.log(data.results);
import requests

url = "https://us-city-crime-statistics-fbi-ucr17.p.rapidapi.com/v1/crime/city"
headers = {
    "X-RapidAPI-Key": "YOUR_KEY_HERE",
    "X-RapidAPI-Host": "us-city-crime-statistics-fbi-ucr17.p.rapidapi.com",
}
params = {"city": "Dayton", "state": "OH", "year": 2024}
data = requests.get(url, headers=headers, params=params).json()
print(data["results"])

Response

{
  "results": [
    {
      "location": "DAYTON",
      "state": "OH",
      "population": 134857,
      "data_year": 2024,
      "data_source": "FBI UCR RETA reta-2024.zip, year 2024",
      "coverage_rate": 1.0,
      "violent_crime":  { "rate_per_100k": 1339.2, "count": 1806 },
      "property_crime": { "rate_per_100k": 4334.2, "count": 5845 },
      "offenses": {
        "murder":              { "rate_per_100k": 29.7,   "count": 40 },
        "robbery":             { "rate_per_100k": 252.9,  "count": 341 },
        "aggravated_assault":  { "rate_per_100k": 940.3,  "count": 1268 },
        "motor_vehicle_theft": { "rate_per_100k": 1330.3, "count": 1794 }
      }
    }
  ]
}

Examples match each product's live API docs. Full schemas, every parameter, and a one-click test console are on each product's docs page.

Provenance first

The same principle runs through every product we build.

Cited to the source

Every record traces back to the primary public filing it came from — California EDD, DOL OFLC, FBI UCR. No black-box scores. You can always see where the data originated.

Normalized & consistent

We do the unglamorous work of reconciling inconsistent public sources into one clean, predictable schema you can build on. Same field names, same types, every time.

Self-serve & metered

No sales calls. Get a key on RapidAPI, query a documented endpoint, and pay only for what you use. Free tier on every product.