GraphCanon updated today · GitHub synced today
Decision brief
GerevAI offers an AI-driven solution for enterprise-wide content and knowledge searching with applications in helpdesk support and tech assistance.
Good fit when
- If your organization needs efficient search capabilities across various technical documents, leveraging AI to provide quick resolutions in tech support scenarios, Gerev is suitable.
- For businesses that require integration with other AI technologies like Confluence or Llama Index for comprehensive internal documentation retrieval.
Avoid when
- If your organization prefers open-source tools without proprietary AI-driven functionalities, consider alternatives as Gerev may not align with purely open-source preference.
- In cases where the specific integrations provided by competing solutions are more aligned with existing enterprise tools beyond Confluence and Llama Index.
- Hosting:
- self hosted - Self-hostable, ensuring full control over the environment in which Gerev operates.
Observed Jul 15, 2026 · Source: enrich:decision_facts
Verify the decision
Maintenance and security
Full trust report- Maintenance
- Dormant (967d since push)
- As of today
- Provenance
- Not a fork · Organization account
- As of today
- Security (OSV)
- No lockfile
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install gerevSimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
GerevAI provides an AI-driven solution for efficient enterprise-wide content and knowledge searching suitable for helpdesk support and tech assistance scenarios.
Capability facts
- Deploy
- Self-host
Source: dockerfile:Dockerfile · Aug 23, 2026
- Docker
- Dockerfile present
Source: dockerfile:Dockerfile · Aug 23, 2026
- Languages
- python
Source: github.language · Aug 23, 2026
Categories
Tags
README
Nvidia for docker
Install nvidia container toolkit on the host machine.
distribution=$(. /etc/os-release;echo $ID$VERSION_ID) \
&& curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add - \
&& curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list
sudo apt-get update
sudo apt-get install -y nvidia-docker2
sudo systemctl restart docker
Run docker
Then run the docker container like so:
Nvidia hardware
docker run --gpus all --name=gerev -p 80:80 -v ~/.gerev/storage:/opt/storage gerev/gerev
For agents
This page has a .md twin and JSON over the API.