arche-core

The identity data engine for Africa.

Arche finds identifying data, helps protect it according to the right jurisdiction, and prepares it for privacy-preserving resolution.

The public arche-core package focuses on three connected jobs:

• Detect identifying data in African text and documents.
• Protect it with jurisdiction-aware masking, tokenization, generalization, dropping, retention, and audit actions.
• Resolve more safely by producing normalized, policy-aware signals such as tokenized IDs, names, phones, and addresses.

Today, Detect and Protect are the lead product surface. Resolution support is intentionally narrow: name matching, tokenized identifiers, and optional Splink-backed workflows for larger linkage tasks.

Warning

arche-core is pre-beta software. It is suitable for research, prototyping, evaluation, benchmarking, and contribution. APIs may change between alpha releases. Do not use it with real personal data until you have completed your own legal, privacy, and security review.

Install

pip install arche-core

Optional extras add heavier capabilities:

pip install "arche-core[doc]"       # PDF, DOCX, PPTX, XLSX, HTML parsing
pip install "arche-core[detect]"    # GLiNER2-PII soft-PII detection
pip install "arche-core[presidio]"  # Microsoft Presidio integration
pip install "arche-core[resolve]"   # Splink + DuckDB resolution support

Quick example

from arche import Pipeline

pipeline = Pipeline(jurisdiction="NG")
result = pipeline.process(
    "Fatima Abdullahi, NIN 12345678901, BVN 22100987654."
)

print(result.redacted_text)
# NAME_... NAME_..., NIN [NIN], BVN [BVN].

for detection in result.detections:
    print(
        detection.category,
        detection.sensitivity_tier.value,
        detection.regulatory_citation,
    )

Same pipeline shape works for the four launch jurisdictions:

Jurisdiction	Policy loaded
NG	NDPA-2023
ZA	POPIA
KE	Kenya DPA
GH	Ghana DPA

What Arche can detect

Area	Current coverage
Government IDs	Nigerian NIN, BVN, TIN, RC, PVC, drivers licence; Kenyan National ID, Huduma, KRA PIN, NHIF; South African ID, tax, passport; Ghana Card, SSNIT, TIN; plus wider African ID patterns
Names and local NER	African name lexicon and equivalence data, with optional GLiNER soft-PII detection
Phones	libphonenumber-backed E.164 normalization across African networks
Addresses	Nigeria and South Africa parser MVP
Digital identifiers	DIDs, Bitcoin addresses, Ethereum addresses
Network identifiers	IPv4 and IPv6 detection with private and special-range flags
Documents	PDF, DOCX, PPTX, XLSX, and HTML parsing via arche-core[doc]

Detect, Protect, Resolve

Detect

Pipeline.process(...) finds identity signals and PII spans in text. With arche-core[doc], Pipeline.process_file(...) parses supported document files and runs the same detection pipeline over extracted text.

Protect

Every detection can carry a category, sensitivity tier, regulatory citation, and policy action. The policy layer maps detections to one of six actions:

Action	Purpose
mask	Replace direct identifiers such as high-risk government IDs
tokenize	Produce deterministic pseudonyms for privacy-preserving joins
drop	Remove data that should not continue through the workflow
generalize	Reduce precision, such as street address to city
audit	Keep an event trail without storing raw PII values
retain	Leave data that the policy permits to pass through

Resolve

Resolution depends on clean, protected signals. Arche helps prepare those signals by normalizing phones, identifying IDs, detecting names, parsing address fragments, and producing deterministic tokens that can become privacy-preserving join keys.

For current resolution workflows, install:

pip install "arche-core[resolve]"

Document scanning

from arche import Pipeline

pipeline = Pipeline(jurisdiction="ZA")
result = pipeline.process_file("dsar_response.pdf")

print(result.summary())
print(result.redacted_text)

Name matching

from arche.match import match

score = match("Mamadou Diallo", "Muhammad Jallow", jurisdiction="NG")
print(score.decision, score.score)

Use this when you need culturally aware name matching before or after PII detection.

Documentation

• Docs: https://unpatterned-labs.github.io/arche/
• Quick start: docs-site/docs/getting-started/quickstart.md
• API reference: docs-site/docs/api/index.md
• Examples: examples/

License

The framework is Apache-2.0. Dataset licensing is documented separately in the dataset cards and repository licensing files.