Accuracy & Volume KPIs

AI matching performance metrics

Period: 2 days

Overall Accuracy

Overall Accuracy
--%
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Accuracy w/o Ref & Repère
--%
sans référence & repère
Perfect Extractions
--%
validés SANS modification
Perfect w/o Ref & Repère
--%
hors référence/repère
Perfect Line Rate
--%
par ligne (measurement)
Perfect Line w/o Ref & Repère
--%
lignes hors ref/repère
Extractions
--
verified in period
Lines (Measurements)
--
total measurements analyzed
High Confidence (>=80%)
--%
Monce conf >= 80%
Verification Rate
--%
verified / total

Article Matching Accuracy

Verre 1
--%
Verre 2
--%
Intercalaire
--%
Remplissage
--%
Faconnage
--%

Dimensions

Quantity
--%
AI extraction vs human correction
Largeur
--%
AI extraction vs human correction
Hauteur
--%
AI extraction vs human correction

Text Extraction & Client Matching

Reference
--%
AI extraction vs human correction
Repere
--%
AI extraction vs human correction
Client
--%
client_matching.nom vs corrected

Accuracy by Factory

Factory Overall Verre 1 Verre 2 Intercalaire Remplissage Faconnage QTY Largeur Hauteur Verified
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Accuracy by Client

Client Overall Verre 1 Verre 2 Intercalaire Faconnage QTY Largeur Hauteur Client Match Verified
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Examples: What Works vs What Doesn't

Correct Matches

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Incorrect Matches

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Monce Expression (Snake Match Types)

How Monce matches queries: Exact (100% synonym match) vs SAT (>=50% lookalike vote) vs Low Conf (<50%)

Field Exact % SAT % Low Conf % Total
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Daily Volume by Factory

Date Total Verified Pending Rate
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Synonym Management

Apply Approved Synonyms

Batch-apply all approved synonyms to Monce models. Duplicates (100% matches) will be skipped.

0 approved

Unmatched queries from verified extractions. Approve suggestions to add them in the next rebuild.

Article Suggestions

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Text Target Article Count Actions
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Client Suggestions

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Text Target Client Count Actions
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Propose New Synonym

Submit a new synonym mapping for admin review.

Methodology

Data Sources

How Accuracy is Calculated

  1. Fetch - Extractions verifiees des N derniers jours avec value_corrected
  2. Extract - Texte corrige par l'humain: value_corrected.measurements[i].verre1, etc.
  3. Ground Truth - Appel batch a Monce API pour obtenir le num_article correct
  4. Compare - Prediction AI (matching[i].verre1.num_article) vs Monce result

Formula

Accuracy = (AI predictions matching Monce) / (Total comparisons) x 100

Fields Analyzed

verre1Article principal (le plus difficile - "black holes" Monce)
verre2Deuxieme vitrage (double/triple vitrage)
intercalaireEspaceur entre vitrages (Warm-edge, Alu...)
remplissageGaz (Argon, Air, Krypton)

Perfect Rate Metrics

Perfect Extraction Rate% of documents (orders) where ALL fields across ALL lines are correct. Strict: a 20-line order with 1 bad field fails entirely.
Perfect Line Rate% of individual measurements (lines) where all evaluated fields are correct. More granular: a failed document can still have 95% perfect lines.
Perfect Line w/o Ref & RepèreSame as Perfect Line Rate but only evaluating article fields (verre1, verre2, intercalaire, remplissage, faconnage). Excludes reference and repère text fields.
Perfect Line Rate = (lines with all fields correct) / (total lines with data) x 100
Invariant: Perfect Line Rate >= Perfect Extraction Rate (always)

Known Limitations