fedcomp-index 2026.4.0

Federal contractor competitive intelligence. Two-axis classification (volume x frequency), four Posture Classes, and classified datasets for every federal contractor.

FedComp Index

Federal contractor competitive intelligence. Classifies every federal contractor in a state into one of four Posture Classes using two-axis thresholds on base contract data, then provides proximity maps, velocity tracking, and pre-classified datasets.

This is the meta-package. It installs:

• fedcomp-index-scoring - posture classification engine
• fedcomp-index-data - pre-classified contractor datasets

Install

pip install fedcomp-index

Usage

from fedcomp_index import classify, classify_contractor, load_state, lookup, PostureClass

# Classify a contractor from two axes
cls = classify(base_dollars=12_000_000, base_contract_count=5)
print(cls)   # PostureClass.CLASS_1

# Get a full result object
result = classify_contractor(base_dollars=12_000_000, base_contract_count=5)
print(result.posture_class)         # PostureClass.CLASS_1
print(result.base_dollars)          # 12000000
print(result.base_contract_count)   # 5

# Load pre-classified data
contractors = load_state("NV")
print(f"{len(contractors)} contractors classified")

# Look up by UEI
c = lookup("CGAKREGGN9J3")
print(c["legal_name"])        # FLEET VEHICLE SOURCE INC
print(c["posture_class"])     # Class 1

Classification methodology (v1.1)

Two axes, no composite score, no weighted sum:

Axis	Threshold	What it measures
Base contract dollars (5yr)	$5M	Volume of competitively won work
Base contract count (5yr)	3	Frequency of distinct wins

"Base contracts" means definitive contracts, purchase orders, and BPA calls. Delivery orders and task orders are excluded from classification.

Posture Class	Volume	Frequency	Profile
Class 1	$5M+	3+ contracts	Systematic winner, repeatable pipeline
Class 2	$5M+	<3 contracts	Concentrated risk, few large awards
Class 3	<$5M	3+ contracts	Growth pipeline, building track record
Class 4	<$5M	<3 contracts	Entry level or dormant

Full methodology: fedcompindex.org/methodology

Packages

Package	What it does
fedcomp-index	Meta-package (this one)
fedcomp-index-scoring	Posture classification engine
fedcomp-index-data	Pre-classified contractor datasets

Data sources

All public federal records:

• USASpending.gov - award history, dollar amounts, agencies, NAICS, PSC
• SAM.gov - entity registration, certifications
• SBA.gov - certification verification

Datasets

• Nevada Federal Contractors (HuggingFace)
• Nevada Federal Contract Awards (HuggingFace)
• Nevada Federal Contractors (Kaggle)

Also available on npm

npm install fedcomp-index

• fedcomp-index - meta-package
• fedcomp-index-scoring - classification engine
• fedcomp-index-data - pre-classified datasets

Links

• Website: https://fedcompindex.org/
• Nevada Rankings: https://fedcompindex.org/nv/
• Methodology: https://fedcompindex.org/methodology/
• Tabularium: https://fedcompindex.org/tabularium/
• FAQ: https://fedcompindex.org/faq/
• Source: https://github.com/fedcompindex/FedCompIndex
• PyPI: https://pypi.org/project/fedcomp-index/
• PyPI (Scoring): https://pypi.org/project/fedcomp-index-scoring/
• PyPI (Data): https://pypi.org/project/fedcomp-index-data/
• HuggingFace: https://huggingface.co/datasets/npetro6/nevada-federal-contractors
• Kaggle: https://www.kaggle.com/datasets/npetro6/nevada-federal-contractors-fedcomp-index

Citation

@software{fedcomp_index,
  title = {FedComp Index},
  author = {FedComp Index},
  url = {https://fedcompindex.org/},
  year = {2026}
}

License

MIT