Comparison
paperless-ai vs EnterpriseRAG-Bench
Verdict
Pick paperless-ai if paperless-ai is a JavaScript-built automated document analyzer for Paperless-ngx that tags documents using OpenAI API and compatible services such as Ollama, Deepseek-r1, and Azure; pick EnterpriseRAG-Bench if enterpriseRAG-Bench specializes in benchmarking RAG models on company internal documents, offering specific evaluation metrics for enterprise-level data.
Markdown twin · paperless-ai alternatives · EnterpriseRAG-Bench alternatives
GraphCanon updated Sep 20, 2026
9views this month
vs
Trust & integrity
| Signal | paperless-ai | EnterpriseRAG-Bench |
|---|---|---|
| Maintenance | Very active (1d since push) As of Sep 20, 2026 · github_public_v1 | Active (16d since push) As of Sep 20, 2026 · github_public_v1 |
| Provenance | Not a fork · Personal account As of Sep 20, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 20, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 15, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- paperless-ai
- Automated document analyzer for Paperless-ngx using OpenAI API and compatible services to tag documents
- EnterpriseRAG-Bench
- Dataset and benchmark for RAG on company internal documents
Stars
- paperless-ai
- 6.0k
- EnterpriseRAG-Bench
- 562
Forks
- paperless-ai
- 331
- EnterpriseRAG-Bench
- 62
Open issues
- paperless-ai
- 56
- EnterpriseRAG-Bench
- 13
Language
- paperless-ai
- JavaScript
- EnterpriseRAG-Bench
- -
Adopt for
- paperless-ai
- Paperless-ai is a JavaScript-built automated document analyzer for Paperless-ngx that tags documents using OpenAI API and compatible services such as Ollama, Deepseek-r1, and Azure.
- EnterpriseRAG-Bench
- EnterpriseRAG-Bench specializes in benchmarking RAG models on company internal documents, offering specific evaluation metrics for enterprise-level data.
Persona
- paperless-ai
- -
- EnterpriseRAG-Bench
- -
Runtime
- paperless-ai
- -
- EnterpriseRAG-Bench
- -
License
- paperless-ai
- MIT
- EnterpriseRAG-Bench
- MIT license allows free usage and modification with attribution.
Last pushed
- paperless-ai
- Sep 19, 2026
- EnterpriseRAG-Bench
- Sep 3, 2026
Categories
- paperless-ai
- Evaluation & Observability, Model Training
- EnterpriseRAG-Bench
- Data & Retrieval, Evaluation & Observability
Trust and health
Maintenance
- paperless-ai
- Very active (96%)
- EnterpriseRAG-Bench
- Active (82%)
Days since push
- paperless-ai
- 1d
- EnterpriseRAG-Bench
- 16d
Open issues (now)
- paperless-ai
- 56
- EnterpriseRAG-Bench
- 13
Stars delta
- paperless-ai
- +68 (30d)
- EnterpriseRAG-Bench
- +73 (30d)
Open issues delta
- paperless-ai
- -7 (30d)
- EnterpriseRAG-Bench
- +4 (30d)
Owner type
- paperless-ai
- User
- EnterpriseRAG-Bench
- Organization
Full report
- paperless-ai
- Trust report
- EnterpriseRAG-Bench
- Trust report
Choose paperless-ai if…
- Tags unique to paperless-ai: ai, automation, gemma, llama.
- Also covers Model Training.
- paperless-ai ships Docker support for self-hosted deployment.
- - When you require integration with Paperless-ngx for managing digital documents automatically with tagging capabilities
When NOT to use paperless-ai
- - For projects that do not involve the management or automatic analysis of digital documents within a Paperless-ngx context
- - In environments where the specific services it integrates with, such as Ollama and Deepseek-r1, are unavailable or unsupported
Choose EnterpriseRAG-Bench if…
- Tags unique to EnterpriseRAG-Bench: benchmark, dataset, enterprise-search, evaluation.
- Also covers Data & Retrieval.
- When you need to evaluate retrieval-augmented generation models specifically for processing extensive and complex enterprise documentation
When NOT to use EnterpriseRAG-Bench
- Avoid if your focus is on general web or public-domain document benchmarking, as EnterpriseRAG-Bench is tuned exclusively for company internal documents
- Do not use if you require a solution that supports languages other than those implied by the existing dataset without further customization
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (clusterzx/paperless-ai) · observed Sep 20, 2026
- GitHub forks (clusterzx/paperless-ai) · observed Sep 20, 2026
- Last push (clusterzx/paperless-ai) · observed Sep 19, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
- GitHub stars (onyx-dot-app/EnterpriseRAG-Bench) · observed Sep 20, 2026
- GitHub forks (onyx-dot-app/EnterpriseRAG-Bench) · observed Sep 20, 2026
- Last push (onyx-dot-app/EnterpriseRAG-Bench) · observed Sep 3, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: paperless-ai 6.0k · EnterpriseRAG-Bench 562 (synced Sep 20, 2026).
Common questions
- What is the difference between paperless-ai and EnterpriseRAG-Bench?
- paperless-ai: Automated document analyzer for Paperless-ngx using OpenAI API and compatible services to tag documents. EnterpriseRAG-Bench: Dataset and benchmark for RAG on company internal documents. See the comparison table for live GitHub stats and shared categories.
- When should I choose paperless-ai over EnterpriseRAG-Bench?
- Choose paperless-ai over EnterpriseRAG-Bench when Tags unique to paperless-ai: ai, automation, gemma, llama; Also covers Model Training; paperless-ai ships Docker support for self-hosted deployment; - When you require integration with Paperless-ngx for managing digital documents automatically with tagging capabilities.
- When should I choose EnterpriseRAG-Bench over paperless-ai?
- Choose EnterpriseRAG-Bench over paperless-ai when Tags unique to EnterpriseRAG-Bench: benchmark, dataset, enterprise-search, evaluation; Also covers Data & Retrieval; When you need to evaluate retrieval-augmented generation models specifically for processing extensive and complex enterprise documentation.
- When should I avoid paperless-ai?
- - For projects that do not involve the management or automatic analysis of digital documents within a Paperless-ngx context - In environments where the specific services it integrates with, such as Ollama and Deepseek-r1, are unavailable or unsupported
- When should I avoid EnterpriseRAG-Bench?
- Avoid if your focus is on general web or public-domain document benchmarking, as EnterpriseRAG-Bench is tuned exclusively for company internal documents Do not use if you require a solution that supports languages other than those implied by the existing dataset without further customization
- Is paperless-ai or EnterpriseRAG-Bench more popular on GitHub?
- paperless-ai has more GitHub stars (5,950 vs 562). Stars measure visibility, not whether either tool fits your constraints.
- Are paperless-ai and EnterpriseRAG-Bench open source?
- Yes - both are open-source projects on GitHub (paperless-ai: MIT, EnterpriseRAG-Bench: MIT).
- Where can I find alternatives to paperless-ai or EnterpriseRAG-Bench?
- GraphCanon lists graph-backed alternatives at paperless-ai alternatives and EnterpriseRAG-Bench alternatives (paperless-ai markdown twin, EnterpriseRAG-Bench markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, paperless-ai or EnterpriseRAG-Bench?
- paperless-ai: Very active. EnterpriseRAG-Bench: Active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for paperless-ai and EnterpriseRAG-Bench?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: paperless-ai trust report; EnterpriseRAG-Bench trust report.