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Gerev

Gerev is an open-source enterprise search application that lets organizations search connected conversations, documents and internal pages using natural-language queries. Its repository describes integrations with collaboration, document and issue-tracking services, plus managed-cloud and Docker-based self-hosted options.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Gerev — OpenViST project profile in RAG & Knowledge Systems.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use Gerev when a team needs natural-language retrieval across its connected workplace knowledge sources, particularly for technical support or internal issue discovery.

Who it is for

  • Help-desk and technical support teams searching internal troubleshooting knowledge.
  • Organizations seeking a unified search experience across supported collaboration, document and issue-tracking sources.
  • Teams evaluating a Python-based, MIT-licensed application for managed-cloud or self-hosted use.

Documented uses

  • Search organizational information with questions in everyday language.
  • Find troubleshooting guidance across connected internal resources.
  • Locate internal issues and conversations without searching each supported source separately.
Before you choose

Requirements & limits

The repository describes a managed-cloud option and a self-hosted community option. Its self-hosted instructions require Docker and describe Nvidia Container Toolkit for the GPU setup, while also providing a CPU-only command.

  • Confirm that the required data sources are among the README’s checked integrations; several other services are listed as unchecked or in progress.
  • Choose between managed cloud, which is described with authentication, multi-user support, a GPU machine and 24/7 support, and self-hosting with Docker.
  • The self-hosted README includes both GPU and CPU-only container commands.
  • The project is written in Python and is licensed under MIT.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Start Gerev with Docker

Launch the self-hosted community container using a documented Docker command.

Before you start

  • A host running Docker.
  • Nvidia hardware and Nvidia’s Docker toolkit for the GPU command; the README also provides a CPU-only command.

Steps

  1. For GPU use, install Nvidia Container Toolkit on the Docker host and restart Docker as described in the repository README.

  2. Run the documented Docker command for Nvidia hardware or use the CPU-only command instead; both publish port 80 and mount ~/.gerev/storage at /opt/storage.

Expected outcome

The Gerev container is started with port 80 exposed and persistent storage mounted at the documented path.

Guide limitations

  • This guide covers starting the container only; it does not document connecting data sources or performing a search.
  • The repository does not provide deployment troubleshooting or environment-specific compatibility guarantees.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
15 October 2026
Original website title
GerevAI/gerev · Official homepage title · retained in its source language
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