Securely connecting siloed content to AI pipelines.
OpenCrawling® is a high-performance enterprise data ingestion and security mapping framework. Powered by Java 25 and Spring Boot 4, it orchestrates secure pipelines using Apache Tika for text extraction, Apache Kafka for queueing, Apache Ozone & S3 for distributed payload storage, Redis for caching, and Ollama for embeddings while preserving document permissions (ACLs).
✔ All services started successfully on local ports.
Java 25Virtual Threads & Structured Concurrency
100%ACL Security & Permission Mapping
Event-DrivenApache Kafka Document Decoupling
Scale-OutDecoupled Embedding Microservice
Designed for Enterprise Security & Scale
Going far beyond simple scraping, OpenCrawling bridges data stores and vector indexes securely.
Enterprise Security First
Built-in authority translation and Access Control List (ACL) mapping. Search engines only return documents that users are explicitly authorized to view.
High Performance & Concurrency
Leverages Java 25 Virtual Threads and Spring Boot. Processes thousands of streams with minimal memory overhead, preventing source system bottlenecks.
AI & RAG Ready Ingestion
Advanced RAG support with flexible chunking and embedding logic. Configure multiple embedding strategies (Ollama, OpenAI, HuggingFace) across diverse vector index backends.
Pluggable SPI Architecture
Simple interfaces for writing custom connectors. Define a new Repository Source, Transformation filter, or Database Output connector in just a few lines of Java.
AI-Powered Observability (AIOps)
Integrates OpenTelemetry (OTel) correlated traces and Micrometer metrics. Automatically translates complex pipeline stack traces into human-readable AI Root Cause Analysis (RCA) and diagnostic recommendations. Learn more →
Auto-Narrativization Copilot
Configured per job or interactive panel. Translates connector schemas into human-readable Mustache narrative templates and mock datasets via Ollama (llama3.2) or OpenAI. Automatically falls back to deterministic generation when AI is offline.
Java Client SDK (`oc-java-client-sdk`)
Strongly typed, fluent Java 25 & Spring Boot 4 client SDK. Programmatically manage ingestion job lifecycles, connector setups, Copilot templates, and AIOps diagnostics with zero third-party HTTP transport bloat. Explore SDK →
Secure Model Context Protocol (MCP) Server
Exposes security-filtered similarity search and document retrieval tools directly to LLMs and AI agent frameworks using the Model Context Protocol (MCP). Enforces user authentication policies (principals and roles) and ACL checks on the server-side to prevent prompt injection and unauthorized data leakage.
Ingestion Architecture
Decoupled, event-driven orchestration with a horizontally scalable Embedding Microservice leveraging Kafka and the Claim Check Pattern.
System Architecture
Hover over or tap any node in the architecture diagram to view how OpenCrawling orchestrates the high-speed data flow and security controls.
Unified Administration Console
Manage repository connectors, monitor Kafka topics, and track ingestion jobs from a sleek, real-time dashboard.
localhost:5173/dashboard
Interactive Admin UI Screencast Walkthrough
Experience real-time pipeline management, job scheduling, AIOps diagnostics, and Auto-Narrativization Copilot in action.
Real-Time Ingestion Telemetry
Track crawling health, active workers, Kafka queue load, and document-indexing throughput at a glance.
Pipeline & Job Scheduling
Schedule, execute, pause, and configure crawling operations. Review historical runs, document success rates, and errors.
Connector Registry Configuration
Set up SharePoint credentials, S3 bucket access policies, database queries, and custom connector metadata properties.
AI & Vector Embedding Mappings
Select RAG embedding models (local Ollama, OpenAI), set custom token text-splitter boundaries, and map schema attributes.
Live System Activity & Audit Logs
Stream real-time JVM telemetry, Kafka partition consumer offsets, active threads, and document security ACL mapping logs.
Live Ingestion Simulator
Simulate real-time ingestion, security mapping, and the new decoupled embedding scale-out pipeline locally in your browser.
Ready to run
📂Crawler
🚇Kafka Broker
⚙️Ingestion (Tika)
🔱oc-embedding-service×1
🧬Vector Writer
Job Console Output
Select a source and click "Run Ingestion Job" to start simulation...
Getting Started in 2 Minutes
Follow these quick steps to get OpenCrawling up and running locally.
# Option 1: Standard Multi-Tier Stack (Backend + Standalone Frontend)
# 1. Start backing services (Postgres, Redis, Kafka, Ollama)
docker compose up -d
# 2. Start pre-built applications from Docker Hub (no compilation)
docker compose -f docker-compose-apps-dockerhub.yml up -d
# 3. (Alternative) Or build from source and run:
docker compose -f docker-compose-apps.yml build
docker compose -f docker-compose-apps.yml up -d
# Option 2: Decoupled Microservices Pipeline (Fully Distributed Workers)
# 1. Run using pre-built Docker Hub images (includes OTel stack)
docker compose -f docker-compose-decoupled-dockerhub.yml up -d
# 2. (Alternative) Or run using pre-built GHCR release images:
docker compose -f docker-compose-decoupled-dist.yml up -d
# 3. (Alternative) Or build from local source and run:
docker compose -f docker-compose-decoupled.yml build
docker compose -f docker-compose-decoupled.yml up -d
# Access points:
# - Standalone Administration Console: http://localhost:3000
# - Secure MCP Server / REST Backend: http://localhost:8080
<!-- Add core connector API to your spring boot application -->
<dependency>
<groupId>org.opencrawling</groupId>
<artifactId>oc-core</artifactId>
<version>1.0.0-SNAPSHOT</version>
</dependency>
<!-- Include FileSystem Repository Connector if required -->
<dependency>
<groupId>org.opencrawling</groupId>
<artifactId>oc-filesystem-repository-connector</artifactId>
<version>1.0.0-SNAPSHOT</version>
</dependency>
// Implement RepositoryConnector interface to create custom sources
public class MyCustomRepositoryConnector implements RepositoryConnector {
@Override
public void connect(Map<String, String> configParams) throws RepositoryConnectionException {
// Establish authentication with target repository
}
@Override
public void scanDocuments(DocumentProcessor processor, JobContext context) {
// Scan documents incrementally and dispatch to processor
for (Document doc : fetchNewDocuments()) {
processor.processDocument(
doc.getId(),
doc.getContentStream(),
doc.getMetadata(),
doc.getAcl() // Synchronize Access Control Lists!
);
}
}
}
Open Ingestion Standard (OIS)
A cross-platform specification for secure enterprise data exchange and configuration.
The Ingestion Manifesto
Enterprise data pipelines suffer from proprietary lock-in and security permission leaks. The OIS specification standardizes document payloads, metadata repositories, and workflow processes—now featuring native integration with the CMIS standard for enterprise document retrieval and the BPMN format for business process workflows—to enable seamless interoperability.
Discover OpenCrawling's new gRPC Internal Transport Layer (oc-grpc-api). Featuring HTTP/2 multiplexing, Protobuf binary payload compression up to 50%, AUTO fallback to HTTP/REST, TLS/mTLS encryption, Admin UI hot-reload, and live diagnostic ping probes.
Learn how OpenCrawling's official Maven Archetypes suite allows developers to instantly scaffold ready-to-build Repository, Output, and Transformation Connectors with Docker Compose overlays and Admin UI integration.
OpenCrawling now natively supports the top open-source BPMN workflow engines: Flowable and Camunda. Discover how oc-flowable-repository-connector and oc-camunda-repository-connector stream process definitions, historic execution variables, and candidate group ACLs into AI pipelines.
Learn how OpenCrawling's Auto-Narrativization Copilot translates structured database schemas and table records into rich natural language Mustache templates and mock datasets using Spring AI, Ollama (llama3.2), and deterministic offline fallbacks.
OpenCrawling now offers full, native support for Apache Ozone (v2.2.0+) as a distributed Claim Check store provider. Learn how combining the Claim Check Pattern with Ozone's S3 Gateway eliminates Kafka payload bottlenecks and scales RAG binary ingestion to petabyte scale.
OpenCrawling now supports Apache Iceberg data lakes as a first-class ingestion source. The new oc-iceberg-repository-connector module scans Iceberg table catalogs (REST, Hive, Hadoop, AWS Glue) and streams structured records directly into the RAG pipeline.
The new oc-alfresco-repository-connector bridges Alfresco Content Services to your AI pipeline via the Alfresco REST API v1. Discover how Java 25 Structured Task Scope enables parallel folder traversal, and how the Claim Check Pattern decouples remote content downloads from the Kafka publish step.
Enterprise Content Management (ECM) integration specialist Luis Cabaceira joins the OpenCrawling core team. Read about his work on repository connectors, CMIS mappings, and secure enterprise document ingestion.
Enterprise search architect and big data veteran Michael Cizmar joins the OpenCrawling core team. Read about his background and his plans to drive event-driven ingestion parallelization and multi-tenant vector writer integrations.
Discover how the new oc-embedding-service microservice separates embedding generation into a dedicated, horizontally scalable unit. Learn how Kafka consumer group partitioning, the EmbeddingModelFactory, and Docker Compose scaling unlock GPU-level throughput without changing the rest of your pipeline.
Learn how OpenCrawling leverages the Model Context Protocol (MCP) and Spring AI to expose secure, enterprise-grade, ACL-filtered knowledge retrieval tools directly to LLM agents.
Enterprise data pipelines suffer from proprietary lock-in and security leaks. Today we are launching OIS—a Zero-Trust, vendor-neutral specification—and its Java 25 reference engine, OpenCrawling. Learn how we preserve ACL security.
A security mapping framework is only as powerful as the repositories it can reach. Share your feedback in our GitHub Roadmap discussions and vote on SharePoint, S3, Qdrant, and Confluence.
Connect & Contribute
We are an open-source organization building the future of secure AI ingestion pipelines.