Same drug. Dozens of listings. One canonical record.
A single medication appears as "Metformin HCl 500mg Tab" in a hospital formulary, "METFORMIN HYDROCHLORIDE 500 MG TABLET" in a PBM feed, and "Glucophage 500mg" in a distributor catalog. Multiply that across thousands of NDCs, generics, and branded equivalents. Fuzzy resolves all of them automatically — and gets smarter with every formulary update.
Brand and generic names fracture your catalog. “Lipitor”, “Atorvastatin Calcium”, and “Atorva 40mg” are the same molecule — your formulary tracks them as three products.
Strength and dosage forms are inconsistent. 500mg, 500 MG, 0.5g, “500-mg tablet” — every source formats potency and form differently.
Every new data source compounds the mess. Each wholesaler, PBM, GPO, or hospital system feed creates exponentially more duplicates and near-duplicates.
Dirty data blocks clinical and financial outcomes. Formulary optimization, 340B compliance, and spend analytics all break without a clean drug product graph.
Why Fuzzy
Pharma-native normalization. Understands NDC formats, brand/generic equivalence, salt forms (HCl, sodium, tartrate), and dosage-form aliases.
Self-improving. Every pharmacist correction trains the system. The same drug match is never decided twice.
Fully explainable. See exactly why every match was made — confidence scores, tier breakdown, reasoning. No black boxes.
Veto fields prevent dangerous false positives. Different strength or dosage form = automatic reject. “Metformin 500mg” never matches “Metformin 1000mg”.
Deeply configurable. Tune matching rules, strength normalization, NDC parsing, and confidence thresholds — every health system’s data is different.
Four-Tier Matching Pipeline
T1
Exact Match — Normalized
Free
T2
Fuzzy Consensus — 3/5 vote
Free
T3
LLM Reasoning — Ambiguous pairs
~$0.001
T4
Human Review — Feedback loop
You
80% free15% LLM5% human
LLM + Human Review
The LLM understands that “Lisinopril/HCTZ 20-12.5” and “Zestoretic 20/12.5mg” are the same combination product. It resolves “Amox-Clav 875” vs “Augmentin 875mg” by reasoning about pharmaceutical naming conventions. Clinical pharmacists handle the final 5% — and every correction is cached permanently so the same pair is never re-decided.
“Atorva Ca 40mg” → “Atorvastatin Calcium 40mg” — LLM maps salt-form abbreviation with 0.94 confidence
Intelligent Industry Warm-Up
Fuzzy learns your domain by asking targeted questions — not generic setup wizards. One answer applies across the entire dataset.
“I found 23 variations of ‘Lisinopril 10mg’. Should ‘Lisinopril/HCTZ 10-12.5mg’ be grouped with plain Lisinopril, or tracked as a separate combination product?”
Your team's expertise stays with you. Fuzzy just learns from it.
Design Partner Pilot
Run Fuzzy against your actual formulary or wholesaler catalog — real results, not synthetic benchmarks
Pharma-specific field mapping tuned to your NDC, SNOMED, or RxNorm schemas
Shape the product roadmap alongside your pharmacy and informatics team’s needs
Early access pricing — locked in before general availability
Let’s see if Fuzzy fits your pharmaceutical data.
30-minute call — we’ll look at your drug catalog matching pain together.