AbgarSim

AbgarSim / sieve-aml

Public

High-performance, open-source sanctions screening/watchlist engine for AML/KYC compliance. Features fuzzy (Jaro-Winkler), phonetic (Double Metaphone), and token-based name matching against OFAC, UN, EU & UK watchlists. Embeddable Java library with Vert.x and Spring Boot server modules, batch screening API, and audit trail support.

abgarsim.github.iosieve-aml aml anti-money-laundering audit-trail batch-screening compliance
11
2
100% credibility
Found Mar 20, 2026 at 11 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Java
AI Summary

An open-source tool that fetches public sanctions watchlists, normalizes the data, and lets you screen names for matches using a command-line interface or web API.

How It Works

1
📰 Discover Sieve

You hear about Sieve, a free tool that checks names against official bad actor watchlists to stay compliant without pricey software.

2
💻 Get it ready

Download the program to your computer and prepare it with a simple setup so it's good to go.

3
📥 Pull watchlists

Let it grab the latest public government watchlists automatically, building your private checker in moments.

4
🔍 Screen a name

Type in a name like 'John Doe' and instantly see if it matches anyone on the lists, with confidence scores.

5
Pick your way
⌨️
Command line

Run checks right from your terminal anytime.

🌐
Web service

Launch a private web checker everyone can use.

✅ Stay safe

Now you screen names privately and reliably, keeping your business compliant without external services.

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Star Growth

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AI-Generated Review

What is sieve-aml?

Sieve-aml is a high performance open source Java library for sanctions screening in AML/KYC workflows. It pulls public watchlists from OFAC, UN, EU, and UK sources, normalizes them into an in-memory index, and matches names using fuzzy, phonetic, and token-based algorithms via an embeddable API. Developers get a ready-to-run CLI for quick screens like `sieve screen "John Doe"` and REST endpoints on Vert.x for throughput or Spring Boot for persistence.

Why is it gaining traction?

It ditches pricey commercial engines with a zero-dependency core that hits high performance benchmarks on Vert.x, handling concurrent screens without breaking a sweat. The dual CLI/API setup plus Docker Compose means instant prototyping, and audit trails keep compliance boxes checked. For AML/KYC against watchlists, it's a lean alternative to bloated SaaS.

Who should use this?

Backend engineers at fintechs integrating real-time name screening into transaction flows. Compliance teams building batch processors for customer onboarding. Java devs needing embeddable matching without vendor lock-in.

Verdict

Grab it if you're prototyping high performance open source AML tools—CLI and API work out of the box with solid docs. At 11 stars and 1.0% credibility, it's early alpha; test coverage claims 90% but expect rough edges on non-OFAC lists.

(187 words)

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