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Piler

Email Security

Open Source
Free Tier
Self-hosted
E
Enterprise
OpenMSP Score
39
34
Reddit Impact Score
Github Score
1M
279Stars
42Forks
2KCommits
OtherLicense
Feb 20, 2026Last commit
Piler is a feature-rich open source email archiving solution that provides a viable alternative to commercial email archiving products. It offers comprehensive email archiving capabilities including legal hold, retention policies, deduplication, digital fingerprinting, and full-text search. Built with a modern microservices architecture, Piler supports deployment on physical servers, VMware, Hyper-V, cloud platforms (AWS, Azure, GCP), and Docker containers. The solution includes a PHP-based GUI with multiple authentication methods (AD/LDAP, SSO, Google OAuth, 2FA, IMAP, POP3) and supports both Google Apps and Office 365 integration. Piler is designed for organizations requiring secure, compliant, and intelligent email archiving with features like ML-powered semantic search, phishing detection, and DLP policies.
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Key Features

Multi-Tenancy

Separates tenant data on file, database, and index levels

Email Archiving

Real-time archiving of all inbound emails with automatic retention rules and legal hold capabilities

Semantic Search

ML-powered search that understands meaning and context, not just keywords

ML Phishing Detection

Advanced machine learning models detect phishing attempts with 95%+ accuracy

Legal Hold

Protect critical emails from deletion with audit trails and compliance-ready preservation

End-to-End Encryption

Encrypted email storage with digital fingerprints to verify message integrity

Pros and Cons

Pros

Open Source

Fully open source with GPL-3.0 license providing transparency and community development

No Vendor Lock-In

Export data anytime in standard RFC-2822 EML format

Deployment Flexibility

Deploy anywhere: physical servers, VMware, Hyper-V, AWS, Azure, GCP, or Docker

Modern Architecture

Container-based microservices design with standard open-source components

ML-Enhanced Security

Built-in PII detection, ML-based phishing detection (95%+ accuracy), and DLP policies

Cons

Learning Curve

Requires technical expertise for initial setup and configuration

Community Support

Primary support through GitHub Issues and Discussions rather than dedicated support team

Feature Comparison

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