Map a compliance requirement to the governing law

Start from a plain-language obligation like “breach notification timelines” and end with the governing sections: federal regulations, agency guidance, and the relevant state rules, each with its citation and a link to the official source. This is the backbone of a RegTech or compliance-mapping feature. Endpoints used: POST /statutes/search, GET /statutes/section/{actId}/body, GET /statutes/coverage (to discover which corpora a jurisdiction has).

Vaquill returns the authoritative regulatory text and links back to the official government source. It supports building a compliance map, it does not render a compliance determination. Pair it with review by qualified counsel.

The flow

Pick the corpora that govern the obligation

A regulatory obligation usually lives across several corpora: CFR (federal regulations), FEDERAL_REGISTER (agency rules), AGENCY_GUIDANCE (rulings and notices), and REGULATION (state administrative rules, paired with a state).

Search each corpus for the obligation

Run POST /statutes/search once per corpus, using the same plain-language query. Collect the top governing sections from each.

Pull the text and group the results

Fetch each section’s full text with GET /statutes/section/{actId}/body, then group by corpusType and jurisdiction so the map reads by source of authority.

Present with citations and official links

Show each section with its citation and the official government URL so a reviewer can open the primary source.

Step 1: search across the regulatory corpora

# Federal regulations (CFR)
curl -X POST https://api.vaquill.ai/api/v1/statutes/search \
  -H "Authorization: Bearer vq_key_..." \
  -H "Content-Type: application/json" \
  -d '{"query": "data breach notification timeline", "corpusType": "CFR", "limit": 5}'

# Federal Register agency rules
curl -X POST https://api.vaquill.ai/api/v1/statutes/search \
  -H "Authorization: Bearer vq_key_..." \
  -H "Content-Type: application/json" \
  -d '{"query": "data breach notification timeline", "corpusType": "FEDERAL_REGISTER", "limit": 5}'

# Agency guidance
curl -X POST https://api.vaquill.ai/api/v1/statutes/search \
  -H "Authorization: Bearer vq_key_..." \
  -H "Content-Type: application/json" \
  -d '{"query": "data breach notification timeline", "corpusType": "AGENCY_GUIDANCE", "limit": 5}'

# A specific state's administrative regulations (e.g. Washington)
curl -X POST https://api.vaquill.ai/api/v1/statutes/search \
  -H "Authorization: Bearer vq_key_..." \
  -H "Content-Type: application/json" \
  -d '{"query": "data breach notification timeline", "corpusType": "REGULATION", "state": "wa", "limit": 5}'

import requests

BASE = "https://api.vaquill.ai/api/v1"
HEADERS = {"Authorization": "Bearer vq_key_..."}


def search(query, corpus_type, state=None, limit=5):
    body = {"query": query, "corpusType": corpus_type, "limit": limit}
    if state:
        body["state"] = state
    resp = requests.post(f"{BASE}/statutes/search", headers=HEADERS, json=body)
    resp.raise_for_status()
    return resp.json()["results"]

const BASE = "https://api.vaquill.ai/api/v1";

async function search(query, corpusType, { state, limit = 5 } = {}) {
  const body = { query, corpusType, limit };
  if (state) body.state = state;
  const resp = await fetch(`${BASE}/statutes/search`, {
    method: "POST",
    headers: {
      Authorization: "Bearer vq_key_...",
      "Content-Type": "application/json",
    },
    body: JSON.stringify(body),
  });
  if (!resp.ok) throw new Error(`search failed: ${resp.status}`);
  return (await resp.json()).results;
}

Not sure which corpora a state has? Call GET /statutes/coverage and read the jurisdiction’s corpora keys, then pass one as corpusType. State regulations (REGULATION) are ingested for a subset of states, so check before you scope to one.

Step 2 and 3: collect, fetch text, and group

Python

import requests
from collections import defaultdict

BASE = "https://api.vaquill.ai/api/v1"
HEADERS = {"Authorization": "Bearer vq_key_..."}


def fetch_body(act_id):
    resp = requests.get(f"{BASE}/statutes/section/{act_id}/body", headers=HEADERS)
    resp.raise_for_status()
    data = resp.json()
    return data.get("plain") if data.get("available") else None


def source_link(result):
    return (
        result.get("htmlUrl")
        or result.get("stateHtmlUrl")
        or result.get("govInfoHtmlUrl")
        or result.get("pdfUrl")
        or result.get("externalUrl")
    )


def map_requirement(obligation, states=None, limit=5):
    # Federal regulatory corpora, plus one REGULATION pass per requested state.
    plan = [
        ("CFR", None),
        ("FEDERAL_REGISTER", None),
        ("AGENCY_GUIDANCE", None),
    ]
    for st in states or []:
        plan.append(("REGULATION", st))

    grouped = defaultdict(list)
    for corpus_type, state in plan:
        for r in search(obligation, corpus_type, state=state, limit=limit):
            text = fetch_body(r["actId"])
            if not text:
                continue  # skip sections with no available text
            # Group key: corpusType, plus the state for state-scoped corpora.
            jurisdiction = (r.get("state") or "federal").upper()
            key = f"{corpus_type} / {jurisdiction}"
            grouped[key].append(
                {
                    "citation": r.get("citation") or r["actId"],
                    "title": r.get("title"),
                    "sourceUrl": source_link(r),
                    "text": text,
                }
            )
    return grouped


def render(obligation, grouped):
    print(f"Governing law for: {obligation}\n")
    for group, sections in grouped.items():
        print(f"== {group} ==")
        for s in sections:
            print(f"  {s['citation']} - {s['title']}")
            print(f"    Source: {s['sourceUrl']}")
        print()


if __name__ == "__main__":
    obligation = "data breach notification timeline"
    result = map_requirement(obligation, states=["wa", "md"])
    render(obligation, result)

A grouped result reads by source of authority:

Governing law for: data breach notification timeline

== CFR / FEDERAL ==
  16 CFR § 318.5 - Notification to the Federal Trade Commission
    Source: https://www.ecfr.gov/...

== AGENCY_GUIDANCE / FEDERAL ==
  ... - Agency guidance on breach reporting
    Source: https://www.govinfo.gov/...

== REGULATION / WA ==
  WAC ... - Notice to affected consumers
    Source: https://app.leg.wa.gov/...

Notes for a production compliance map

Feed the grouped sections into an LLM for a summary

Once you have the grouped, cited text, you can pass it to an LLM in your stack to produce a plain-language summary of each obligation, one that cites each section and links its official source. Use the strict grounding pattern in Ground an LLM answer in statutes so the summary quotes only the retrieved regulatory text.

Scope state regulations deliberately

REGULATION is state-scoped: always pair it with a two-letter state code. Coverage spans a subset of states and expands weekly, so drive the state list from GET /statutes/coverage rather than assuming every state is present.

Keep the official link on every row

Each result carries source URLs (htmlUrl, stateHtmlUrl, govInfoHtmlUrl, pdfUrl, and others; any may be null). Surface the first present link on every mapped section so a reviewer can open the primary source and confirm the text.

Ground an LLM answer (RAG)

Summarize the mapped obligations with strict, cited grounding.

Resolve a citation

Verify a specific regulation citation and pull its text.

Grounding LLMs

The principles behind grounding legal AI on primary sources.

API Coverage

Which corpora and jurisdictions are ingested, with live counts.

Get Started

Core Concepts

Working with the API

Data

Grounding AI

Recipes

Use Cases

Resources

Map a compliance requirement to the governing law

The flow

Step 1: search across the regulatory corpora

Step 2 and 3: collect, fetch text, and group

Notes for a production compliance map

Ground an LLM answer (RAG)

Resolve a citation

Grounding LLMs

API Coverage

​The flow

​Step 1: search across the regulatory corpora

​Step 2 and 3: collect, fetch text, and group

​Notes for a production compliance map

​Related

Ground an LLM answer (RAG)

Resolve a citation

Grounding LLMs

API Coverage

The flow

Step 1: search across the regulatory corpora

Step 2 and 3: collect, fetch text, and group

Notes for a production compliance map

Related