--- title: "paperless-ai vs dataroom" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/clusterzx-paperless-ai-vs-hanxiao-dataroom" tools: ["clusterzx-paperless-ai", "hanxiao-dataroom"] --- # paperless-ai vs dataroom *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 dataroom if dataroom is an LLM research platform built for experimenting with self-hosted data using Qwen3.6 in conjunction with Pi. [paperless-ai](https://clusterzx.github.io/paperless-ai/) reports 6.0k GitHub stars, 331 forks, and 56 open issues, last pushed Sep 19, 2026. [dataroom](https://dataroom.hanxiao.io) has 193 stars, 17 forks, and 3 open issues, last pushed Jun 20, 2026. Figures are from public GitHub metadata via [paperless-ai's repository](https://github.com/clusterzx/paperless-ai) and [dataroom's repository](https://github.com/hanxiao/dataroom). | | [paperless-ai](/tools/clusterzx-paperless-ai.md) | [dataroom](/tools/hanxiao-dataroom.md) | | --- | --- | --- | | Tagline | Automated document analyzer for Paperless-ngx using OpenAI API and compatible services to tag documents | Local LLM research harness for querying Pi with Qwen3.6 | | Stars | 5,950 | 193 | | Forks | 331 | 17 | | Open issues | 56 | 3 | | Language | JavaScript | Python | | 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. | Dataroom is an LLM research platform built for experimenting with self-hosted data using Qwen3.6 in conjunction with Pi. | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT | | Categories | Evaluation & Observability, Model Training | LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [paperless-ai](/tools/clusterzx-paperless-ai.md) | [dataroom](/tools/hanxiao-dataroom.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Slowing (36%) | | Days since push | 1d | 91d | | Open issues (now) | 56 | 3 | | Stars delta | +68 (30d) | +5 (30d) | | Open issues delta | -7 (30d) | 0 (30d) | | Full report | [trust report](/tools/clusterzx-paperless-ai/trust.md) | [trust report](/tools/hanxiao-dataroom/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: dataroom - **Adopt for:** Dataroom is an LLM research platform built for experimenting with self-hosted data using Qwen3.6 in conjunction with Pi. ## Choose when ### Choose paperless-ai if… - paperless-ai is primarily JavaScript; dataroom is Python. - Tags unique to paperless-ai: ai, automation, gemma, llama. - Also covers Evaluation & Observability. - - When you require integration with Paperless-ngx for managing digital documents automatically with tagging capabilities ### Choose dataroom if… - dataroom is primarily Python; paperless-ai is JavaScript. - Tags unique to dataroom: harness, local-llm, pi, qwen3.6. - Also covers LLM Frameworks. - When you need to run experiments on locally hosted datasets, as dataroom specifically supports querying Pi with Qwen3.6. ## 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 dataroom - Avoid using this tool if you require real-time access to a wide variety of datasets outside of what can be locally hosted. - Do not use it if your project demands integration with other cloud-based AI tools or services, as dataroom focuses on local infrastructure. ## Common questions ### What is the difference between paperless-ai and dataroom? paperless-ai: Automated document analyzer for Paperless-ngx using OpenAI API and compatible services to tag documents. dataroom: Local LLM research harness for querying Pi with Qwen3.6. See the comparison table for live GitHub stats and shared categories. ### When should I choose paperless-ai over dataroom? Choose paperless-ai over dataroom when paperless-ai is primarily JavaScript; dataroom is Python; Tags unique to paperless-ai: ai, automation, gemma, llama; Also covers Evaluation & Observability; - When you require integration with Paperless-ngx for managing digital documents automatically with tagging capabilities. ### When should I choose dataroom over paperless-ai? Choose dataroom over paperless-ai when dataroom is primarily Python; paperless-ai is JavaScript; Tags unique to dataroom: harness, local-llm, pi, qwen3.6; Also covers LLM Frameworks; When you need to run experiments on locally hosted datasets, as dataroom specifically supports querying Pi with Qwen3.6. ### 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 dataroom? Avoid using this tool if you require real-time access to a wide variety of datasets outside of what can be locally hosted. Do not use it if your project demands integration with other cloud-based AI tools or services, as dataroom focuses on local infrastructure. ### Is paperless-ai or dataroom more popular on GitHub? paperless-ai has more GitHub stars (5,950 vs 193). Stars measure visibility, not whether either tool fits your constraints. ### Are paperless-ai and dataroom open source? Yes - both are open-source projects on GitHub (paperless-ai: MIT, dataroom: MIT). ### Where can I find alternatives to paperless-ai or dataroom? GraphCanon lists graph-backed alternatives at [paperless-ai alternatives](/tools/clusterzx-paperless-ai/alternatives) and [dataroom alternatives](/tools/hanxiao-dataroom/alternatives) ([paperless-ai markdown twin](/tools/clusterzx-paperless-ai/alternatives.md), [dataroom markdown twin](/tools/hanxiao-dataroom/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-hanxiao-dataroom.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, paperless-ai or dataroom? paperless-ai: Very active. dataroom: Slowing. 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 dataroom? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [paperless-ai trust report](/tools/clusterzx-paperless-ai/trust); [dataroom trust report](/tools/hanxiao-dataroom/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/_