GraphCanon updated Sep 20, 2026 · GitHub synced Sep 20, 2026
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Decision brief
Korvus is an SDK leveraging the Retrieval-Augmented Generation (RAG) pipeline within Postgres database operations, supporting multiple programming languages.
Good fit when
- You require seamless integration of AI capabilities into data retrieval actions performed on a Postgres database.
- Need to implement RAG functionality in your project but desire simplicity and efficiency by leveraging a single-query approach.
Avoid when
- You seek a solution that operates beyond the Postgres ecosystem, as Korvus specifically integrates with this type of database.
- If your project necessitates highly specialized RAG implementations without leveraging existing databases for retrieval tasks.
- Requirements:
- Compatible programming languages include Rust, Python, JavaScript, and C.
Observed Jul 12, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Dormant (597d since push)
- As of Sep 20, 2026
- Provenance
- Not a fork · Organization account
- As of Sep 20, 2026
- Security (OSV)
- No lockfile
- As of Jul 11, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
cargo add korvus crates.ioSimilar 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
Korvus is an SDK for search over Postgres that integrates the Retrieval-Augmented Generation (RAG) pipeline. It supports multiple programming languages and focuses on embedding AI capabilities within data retrieval operations.
Capability facts
- Languages
- rust
Source: github.language · Sep 20, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Sep 20, 2026)
```python from korvus import Collection, PipelineSource link
Tags
README
🏁 Quick Start 1. Install Korvus: 2. Set the env variable: 3. Initialize a Collection and Pipeline: 4. Insert documents: 5. Perform RAG
For agents
This page has a .md twin and JSON over the API.