--- title: "paperless-ai vs llm-app" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/clusterzx-paperless-ai-vs-pathwaycom-llm-app" tools: ["clusterzx-paperless-ai", "pathwaycom-llm-app"] --- # paperless-ai vs llm-app *GraphCanon updated Sep 20, 2026* ## 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 llm-app if llm-app offers cloud templates for RAG, AI pipelines, and enterprise search, supporting integration with various data sources like Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and real-time data APIs. [paperless-ai](https://clusterzx.github.io/paperless-ai/) reports 6.0k GitHub stars, 331 forks, and 56 open issues, last pushed Sep 19, 2026. [llm-app](https://pathway.com/developers/templates/) has 59k stars, 1.5k forks, and 8 open issues, last pushed Jul 5, 2026. Figures are from public GitHub metadata via [paperless-ai's repository](https://github.com/clusterzx/paperless-ai) and [llm-app's repository](https://github.com/pathwaycom/llm-app). | | [paperless-ai](/tools/clusterzx-paperless-ai.md) | [llm-app](/tools/pathwaycom-llm-app.md) | | --- | --- | --- | | Tagline | Automated document analyzer for Paperless-ngx using OpenAI API and compatible services to tag documents | Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data | | Stars | 5,950 | 58,920 | | Forks | 331 | 1,498 | | Open issues | 56 | 8 | | Language | JavaScript | Jupyter Notebook | | Adopt for | 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. | llm-app offers cloud templates for RAG, AI pipelines, and enterprise search, supporting integration with various data sources like Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and real-time data APIs. | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT License | | Categories | Evaluation & Observability, Model Training | Data & Retrieval, Evaluation & Observability, Inference & Serving, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [paperless-ai](/tools/clusterzx-paperless-ai.md) | [llm-app](/tools/pathwaycom-llm-app.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Steady (60%) | | Days since push | 1d | 74d | | Open issues (now) | 56 | 8 | | Stars delta | +68 (30d) | -117 (30d) | | Open issues delta | -7 (30d) | 0 (30d) | | Owner type | User | Organization | | Full report | [trust report](/tools/clusterzx-paperless-ai/trust.md) | [trust report](/tools/pathwaycom-llm-app/trust.md) | ## Decision facts: paperless-ai - **Adopt for:** 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. ## Decision facts: llm-app - **Pricing:** freemium - The repository is open-source under the MIT License, but additional services or support might incur costs. - **Requirements:** Min 4 GB RAM; Requires Docker; Requires Docker for running the cloud templates.; Supports integration with a variety of data sources including Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and real-time data APIs. - **Adopt for:** llm-app offers cloud templates for RAG, AI pipelines, and enterprise search, supporting integration with various data sources like Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and real-time data APIs. - **License detail:** MIT License ## Choose when ### Choose paperless-ai if… - paperless-ai is primarily JavaScript; llm-app is Jupyter Notebook. - Tags unique to paperless-ai: ai, automation, gemma, llama. - paperless-ai ships Docker support for self-hosted deployment. - - When you require integration with Paperless-ngx for managing digital documents automatically with tagging capabilities ### Choose llm-app if… - llm-app is primarily Jupyter Notebook; paperless-ai is JavaScript. - Pricing: The repository is open-source under the MIT License, but additional services or support might incur costs.. - Requirements: Min 4 GB RAM; Requires Docker; Requires Docker for running the cloud templates.; Supports integration with a variety of data sources including Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and real-time data APIs.. - Tags unique to llm-app: chatbot, hugging-face, llm, llm-local. - Also covers Data & Retrieval, Inference & Serving. - When you need ready-to-run cloud templates for RAG, AI pipelines, and enterprise search that integrate seamlessly with data sources such as Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and real-ti ## 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 ## When NOT to use llm-app - Avoid using llm-app if your project does not require integration with specific data sources like Sharepoint or Google Drive, as the tool's strength lies in its broad data source support. - Do not use llm-app if you are looking for a tool that focuses solely on model training or inference without the need for cloud templates or enterprise search capabilities. ## Common questions ### What is the difference between paperless-ai and llm-app? paperless-ai: Automated document analyzer for Paperless-ngx using OpenAI API and compatible services to tag documents. llm-app: Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. See the comparison table for live GitHub stats and shared categories. ### When should I choose paperless-ai over llm-app? Choose paperless-ai over llm-app when paperless-ai is primarily JavaScript; llm-app is Jupyter Notebook; Tags unique to paperless-ai: ai, automation, gemma, llama; 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 llm-app over paperless-ai? Choose llm-app over paperless-ai when llm-app is primarily Jupyter Notebook; paperless-ai is JavaScript; Pricing: The repository is open-source under the MIT License, but additional services or support might incur costs.; Requirements: Min 4 GB RAM; Requires Docker; Requires Docker for running the cloud templates.; Supports integration with a variety of data sources including Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and real-time data APIs.; Tags unique to llm-app: chatbot, hugging-face, llm, llm-local; Also covers Data & Retrieval, Inference & Serving; When you need ready-to-run cloud templates for RAG, AI pipelines, and enterprise search that integrate seamlessly with data sources such as Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and real-ti. ### 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 llm-app? Avoid using llm-app if your project does not require integration with specific data sources like Sharepoint or Google Drive, as the tool's strength lies in its broad data source support. Do not use llm-app if you are looking for a tool that focuses solely on model training or inference without the need for cloud templates or enterprise search capabilities. ### Is paperless-ai or llm-app more popular on GitHub? llm-app has more GitHub stars (58,920 vs 5,950). Stars measure visibility, not whether either tool fits your constraints. ### Are paperless-ai and llm-app open source? Yes - both are open-source projects on GitHub (paperless-ai: MIT, llm-app: MIT). ### Where can I find alternatives to paperless-ai or llm-app? GraphCanon lists graph-backed alternatives at [paperless-ai alternatives](/tools/clusterzx-paperless-ai/alternatives) and [llm-app alternatives](/tools/pathwaycom-llm-app/alternatives) ([paperless-ai markdown twin](/tools/clusterzx-paperless-ai/alternatives.md), [llm-app markdown twin](/tools/pathwaycom-llm-app/alternatives.md)), 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](/compare/clusterzx-paperless-ai-vs-pathwaycom-llm-app.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, paperless-ai or llm-app? paperless-ai: Very active. llm-app: Steady. 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 llm-app? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [paperless-ai trust report](/tools/clusterzx-paperless-ai/trust); [llm-app trust report](/tools/pathwaycom-llm-app/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=clusterzx-paperless-ai`](/api/graphcanon/graph?tool=clusterzx-paperless-ai) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_