Comparison
dataroom vs deep-searcher
Verdict
Pick dataroom if dataroom is an LLM research platform built for experimenting with self-hosted data using Qwen3.6 in conjunction with Pi; pick deep-searcher if deepSearcher is an open-source tool for reasoning and searching on private data, using vector databases and LLM integrations in Python under Apache-2.0 license.
Markdown twin · dataroom alternatives · deep-searcher alternatives
GraphCanon updated Sep 20, 2026
13views this month
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Trust & integrity
| Signal | dataroom | deep-searcher |
|---|---|---|
| Maintenance | Slowing (91d since push) As of Sep 20, 2026 · github_public_v1 | Slowing (272d since push) As of Aug 18, 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 Aug 18, 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
- dataroom
- Local LLM research harness for querying Pi with Qwen3.6
- deep-searcher
- Open Source Deep Research Alternative to Reason and Search on Private Data.
Stars
- dataroom
- 193
- deep-searcher
- 8.1k
Forks
- dataroom
- 17
- deep-searcher
- 775
Open issues
- dataroom
- 3
- deep-searcher
- 53
Language
- dataroom
- Python
- deep-searcher
- Python
Adopt for
- dataroom
- Dataroom is an LLM research platform built for experimenting with self-hosted data using Qwen3.6 in conjunction with Pi.
- deep-searcher
- DeepSearcher is an open-source tool for reasoning and searching on private data, using vector databases and LLM integrations in Python under Apache-2.0 license.
Persona
- dataroom
- -
- deep-searcher
- -
Runtime
- dataroom
- -
- deep-searcher
- -
License
- dataroom
- MIT
- deep-searcher
- Apache-2.0
Last pushed
- dataroom
- Jun 20, 2026
- deep-searcher
- Nov 19, 2025
Categories
- dataroom
- LLM Frameworks, Model Training
- deep-searcher
- AI Agents, LLM Frameworks, Vector Databases
Trust and health
Days since push
- dataroom
- 91d
- deep-searcher
- 272d
Open issues (now)
- dataroom
- 3
- deep-searcher
- 53
Stars delta
- dataroom
- +5 (30d)
- deep-searcher
- +59 (30d)
Owner type
- dataroom
- User
- deep-searcher
- Organization
Full report
- dataroom
- Trust report
- deep-searcher
- Trust report
Choose dataroom if…
- License: dataroom is MIT, deep-searcher is Apache-2.0.
- Tags unique to dataroom: harness, local-llm, pi, qwen3.6.
- Also covers Model Training.
- When you need to run experiments on locally hosted datasets, as dataroom specifically supports querying Pi with Qwen3.6.
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.
Choose deep-searcher if…
- License: deep-searcher is Apache-2.0, dataroom is MIT.
- Tags unique to deep-searcher: agent, agentic-rag, deep-research, llm.
- Also covers AI Agents, Vector Databases.
- When you require custom search and reasoning capabilities on your private datasets with integration of multiple LLMs like Claude or Qwen3.
When NOT to use deep-searcher
- Avoid if your project demands proprietary solutions, as DeepSearcher is open-source and may not be suitable for closed systems.
- Not ideal when a single vector database suffices; DeepSearcher supports multiple databases which might be overkill and complicate setup unnecessarily.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (hanxiao/dataroom) · observed Sep 20, 2026
- GitHub forks (hanxiao/dataroom) · observed Sep 20, 2026
- Last push (hanxiao/dataroom) · observed Jun 20, 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 (zilliztech/deep-searcher) · observed Sep 20, 2026
- GitHub forks (zilliztech/deep-searcher) · observed Sep 20, 2026
- Last push (zilliztech/deep-searcher) · observed Nov 19, 2025
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: dataroom 193 · deep-searcher 8.1k (synced Sep 20, 2026).
Common questions
- What is the difference between dataroom and deep-searcher?
- dataroom: Local LLM research harness for querying Pi with Qwen3.6. deep-searcher: Open Source Deep Research Alternative to Reason and Search on Private Data.. See the comparison table for live GitHub stats and shared categories.
- When should I choose dataroom over deep-searcher?
- Choose dataroom over deep-searcher when License: dataroom is MIT, deep-searcher is Apache-2.0; Tags unique to dataroom: harness, local-llm, pi, qwen3.6; Also covers Model Training; When you need to run experiments on locally hosted datasets, as dataroom specifically supports querying Pi with Qwen3.6.
- When should I choose deep-searcher over dataroom?
- Choose deep-searcher over dataroom when License: deep-searcher is Apache-2.0, dataroom is MIT; Tags unique to deep-searcher: agent, agentic-rag, deep-research, llm; Also covers AI Agents, Vector Databases; When you require custom search and reasoning capabilities on your private datasets with integration of multiple LLMs like Claude or Qwen3.
- 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.
- When should I avoid deep-searcher?
- Avoid if your project demands proprietary solutions, as DeepSearcher is open-source and may not be suitable for closed systems. Not ideal when a single vector database suffices; DeepSearcher supports multiple databases which might be overkill and complicate setup unnecessarily.
- Is dataroom or deep-searcher more popular on GitHub?
- deep-searcher has more GitHub stars (8,060 vs 193). Stars measure visibility, not whether either tool fits your constraints.
- Are dataroom and deep-searcher open source?
- Yes - both are open-source projects on GitHub (dataroom: MIT, deep-searcher: Apache-2.0).
- Where can I find alternatives to dataroom or deep-searcher?
- GraphCanon lists graph-backed alternatives at dataroom alternatives and deep-searcher alternatives (dataroom markdown twin, deep-searcher 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, dataroom or deep-searcher?
- dataroom: Slowing. deep-searcher: 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 dataroom and deep-searcher?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: dataroom trust report; deep-searcher trust report.