Legal Research: Search API for Case Monitoring
Use search APIs for legal case monitoring. Track court filings, regulatory updates, and legal news automatically.
Legal professionals track cases, regulatory changes, and industry news across dozens of sources. A junior associate might spend 2-3 hours daily monitoring court dockets, regulatory agency websites, and legal news outlets. A search API can automate the monitoring layer: run scheduled queries, flag new results, and deliver summaries. But it is not a replacement for Westlaw, LexisNexis, or any legal research database. Those tools have verified case law, headnotes, and citator services that no web search can match.
What web search can monitor
- Court opinions published on public court websites
- Regulatory agency press releases and proposed rules
- Legal news from outlets like Law360, Reuters Legal, Bloomberg Law
- Company-specific litigation news
- Competitor patent filings published on USPTO
What web search cannot do
- Full-text case law search with proper citation indexing
- Shepardize or KeyCite a case to check if it is still good law
- Access paywalled court filings (PACER, state court systems)
- Provide verified legal authority for court submissions
Building a case monitoring pipeline
import requests, os, json, datetime
HEADERS = {"x-api-key": os.environ["SCAVIO_API_KEY"]}
API_URL = "https://api.scavio.dev/api/v1/search"
def monitor_case(case_name: str, party_names: list) -> dict:
"""Monitor a case for new developments."""
queries = [
f'"{case_name}" court ruling 2026',
f'"{case_name}" settlement',
]
for party in party_names:
queries.append(f'"{party}" lawsuit 2026')
all_results = []
for q in queries:
resp = requests.post(API_URL, headers=HEADERS,
json={"query": q, "num_results": 5}, timeout=10)
results = resp.json().get("results", [])
all_results.extend([
{
"query": q,
"title": r["title"],
"url": r["url"],
"snippet": r.get("snippet", ""),
}
for r in results
])
# Deduplicate by URL
seen = set()
unique = []
for r in all_results:
if r["url"] not in seen:
seen.add(r["url"])
unique.append(r)
return {
"case": case_name,
"date": datetime.date.today().isoformat(),
"results": unique,
}Regulatory change tracker
def track_regulatory_changes(agencies: dict) -> list:
"""Track regulatory changes across agencies."""
updates = []
for agency, topics in agencies.items():
for topic in topics:
resp = requests.post(API_URL, headers=HEADERS,
json={"query": f"{agency} {topic} proposed rule 2026",
"num_results": 5}, timeout=10)
for r in resp.json().get("results", []):
updates.append({"agency": agency, "topic": topic,
"title": r["title"], "url": r["url"]})
return updates
changes = track_regulatory_changes({
"SEC": ["crypto regulation", "climate disclosure rule"],
"FTC": ["AI regulation", "noncompete ban"],
})
for c in changes:
print(f"[{c['agency']}] {c['title']}")Alert system for new results
import hashlib
SEEN_FILE = "seen_results.json"
def load_seen():
try:
with open(SEEN_FILE) as f:
return set(json.load(f))
except FileNotFoundError:
return set()
def check_new_results(results: list) -> list:
"""Return only results not seen before."""
seen = load_seen()
new_results = []
for r in results:
url_hash = hashlib.md5(r["url"].encode()).hexdigest()
if url_hash not in seen:
new_results.append(r)
seen.add(url_hash)
with open(SEEN_FILE, "w") as f:
json.dump(list(seen), f)
return new_resultsCost for a small law firm
Monitoring 10 active cases with 3 queries each, daily: 30 searches/day. Regulatory tracking across 4 agencies, 3 topics each, weekly: 12 searches/week. Monthly total: roughly 950 searches. At $0.005/credit: $4.75/mo. Compare to a junior associate spending 2 hours daily at $150/hr: $6,600/mo in billable time. The search API handles the monitoring; the associate reviews flagged results and does the actual legal analysis.
Ethical and practical boundaries
Web search results are not verified legal authority. Never cite a web search result in a court filing without verifying it in Westlaw or Lexis. Use this tool for awareness and monitoring, not for legal research that goes into briefs or opinions. The monitoring pipeline tells you "something happened" -- the legal database tells you what it means legally. Also note that some court websites restrict automated access, and a search API only returns publicly indexed results, not sealed filings.