A Wrong Address on a 911 Call Can Be Fatal

When someone calls 911, seconds matter. The dispatcher has to convert a spoken, panicked, often incomplete address into an exact location — fast enough to route first responders before the situation gets worse.

But callers under stress don’t give clean addresses. They say “the corner of MLK and Fifth.” They give apartment numbers out of order. They reference landmarks instead of street addresses. They say “Main Street” in a city with three Main Streets across different neighborhoods.

A wrong parse doesn’t mean a minor delay. It means responders go to the wrong location. In emergency services, that delay can be the difference between life and death.

The Scale of the Problem

The US has over 6,000 Public Safety Answering Points (PSAPs) handling more than 240 million 911 calls per year. Studies show that address-related errors contribute to misdirected dispatches in a significant percentage of calls, with each misdirect adding critical minutes to response times.

Modern Computer-Aided Dispatch (CAD) systems validate caller addresses against a master address database. But these systems choke on the gap between how people report addresses and how databases store them. “900 5th ave apt 12c seattle wa” needs to become a precise, structured record before the system can route it — and it needs to happen in milliseconds, not minutes.

The dispatcher doesn’t have time to manually reformat. And they shouldn’t have to.

The Fix: Parse Free-Form Input Instantly

Address standardization bridges the gap between how humans report locations and how dispatch systems consume them. GoodVat’s Address Standardization API parses free-form, messy, panicked input into structured components and canonical expansions — immediately surfacing what’s there and what’s missing.

curl -X POST "https://api.goodvat.com/v1/address/normalize" \
  -H "Authorization: Bearer $GOODVAT_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{ "query": "900 5th ave apt 12c seattle wa" }'

{
  "houseNumber": "900",
  "road": "5th ave",
  "unit": "apt 12c",
  "city": "seattle",
  "state": "wa",
  "country": "USA",
  "expansions": [
    "900 5th avenue apartment 12c seattle wa usa",
    "900 5th avenue apartment 12c seattle washington usa"
  ]
}

houseNumber, road, unit — pinpoints the exact apartment, not just the building. The expansions array feeds computer-aided dispatch (CAD) search indexing with fully expanded abbreviations ("5th Ave" → "5th Avenue", "apt" → "apartment"). city and state confirm the location falls within the responding jurisdiction. Missing postcode? The system flags it immediately so the dispatcher can ask a follow-up question.

10ms p99 response time. That’s the kind of latency that disappears into a dispatch workflow. 200+ countries for international emergency services. $5/mo unlimited — because pricing per call makes no sense in a context where volume is unpredictable and every call matters.

Every Second Counts

Emergency dispatch has zero tolerance for ambiguity and zero budget for delay. A standardization layer between the call-taker and the CAD system catches formatting issues before they become routing errors.

Read the docs and see how standardization fits into your dispatch pipeline.