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Accuracy

The proof is in the Accuracy Score.

Anyone can claim their AI is accurate. We publish the rubric, ask a real multi-document council question, and score every answer the same way — including our own.

Accuracy Score
Madison Ai95%
Other assistants · average of 347%
The test

One question. Twelve months of packets.

A question no single document answers — it has to be assembled from a year of minutes, then counted correctly.

Question

Across all the council meetings in these minutes, how many total residential housing units were approved through public hearing votes?

Context
12 months of packets/minutes
Correct answer
928 units across 7 hearings
Accuracy Score
  • Copilot8%
  • ChatGPT54%
  • Claude80%
  • Madison Ai95%

Scores on this question, graded against the five dimensions below.

The rubric

The 5 dimensions of an Accuracy Score.

Every answer is graded on the same five dimensions, weighted to what a government actually needs to defend a decision.

  • Correctness
    Is the answer correct?
    30%
  • Completeness
    All key facts included?
    30%
  • Faithfulness
    Backed by docs?
    20%
  • Retrieval
    Found the right docs
    10%
  • Authority
    Used official records?
    10%

How the score works

Accuracy Score
A weighted sum of all five dimensions.
Our target
90%+ on every question.
Automatic fail
Any factual error caps the score at 70% — no matter how well the answer scores everywhere else.
Why the gap

No magic wand. Just hard work.

The same question, run two ways — and the difference is architecture, not prompting.

Drop 24 files into an LLM

The workaround most teams try first.

  • Still time-intensive. Staff re-upload, re-prompt, and re-verify every single time.

  • Inconsistent. Same question, different answer. Capped at ~20 files at a time.

  • Not trustworthy. No grounding, no citations. Nothing you can take to the dais or present to a citizen.

Madison Memory + Intelligence

Two layers, built for the whole task.

Layer 1 — Madison Memory Your single source of truth.
  1. Connect
  2. Convert
  3. Organize
  4. Ground

PDFs · Tabular · GIS · Permit data · ERP · Decades of files/decisions

Layer 2 — Madison Intelligence Agents that complete the whole task.
  1. Analyze
  2. Synthesize
  3. Output
  4. Cite Work

Live in 65+ local governments

Washoe County, Nevada
City of Reno, Nevada
Carson City, Nevada
City of Fernley, Nevada
Northern Nevada Public Health
Lake Tahoe
City of Aspen, Colorado
Pitkin County, Colorado
City of Golden, Colorado
City of Fresno, California
City of Pasadena, California
City of Beverly Hills, California
City of Sunnyvale, California
City of Corona, California
City of San Leandro, California
City of Los Altos, California
Las Virgenes Municipal Water District
Valley Water
City of Chanhassen, Minnesota
Grand Prairie, Texas
Town of Addison, Texas
St. Johns County, Florida
Surry County, North Carolina
Washoe County, Nevada
City of Reno, Nevada
Carson City, Nevada
City of Fernley, Nevada
Northern Nevada Public Health
Lake Tahoe
City of Aspen, Colorado
Pitkin County, Colorado
City of Golden, Colorado
City of Fresno, California
City of Pasadena, California
City of Beverly Hills, California
City of Sunnyvale, California
City of Corona, California
City of San Leandro, California
City of Los Altos, California
Las Virgenes Municipal Water District
Valley Water
City of Chanhassen, Minnesota
Grand Prairie, Texas
Town of Addison, Texas
St. Johns County, Florida
Surry County, North Carolina

Run the same question against your own record.

We’ll load Madison with a sample of your files and score the answers in front of you.

Book a demo See how we handle your data
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