Home/Compare/WeKnora vs deep-searcher

Comparison

WeKnora vs deep-searcher

Verdict

Pick WeKnora if weKnora is an open-source LLM knowledge platform that transforms raw documents into a queryable RAG, autonomous reasoning agent, and self-maintaining Wiki. It is built in Go and offers flexibility through its Docker Com포; 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.

Markdown twin · WeKnora alternatives · deep-searcher alternatives

GraphCanon updated 3d

WeKnora logo

WeKnora

Tencent/WeKnora

20kpushed Aug 16, 2026
vs
deep-searcher logo

deep-searcher

zilliztech/deep-searcher

8.1kpushed Nov 19, 2025

Trust & integrity

SignalWeKnoradeep-searcher
Maintenance
Very active (2d since push)
As of 3d · github_public_v1
Slowing (272d since push)
As of 3d · github_public_v1
Provenance
Not a fork · Organization account
As of 3d · github_public_v1
Not a fork · Organization account
As of 3d · github_public_v1
OSV dependency advisories
No published findings from this source as of 2026-07-11
As of 1mo · osv@v1
No lockfile (source not queried)
As of 1mo · 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

WeKnora
Open-source LLM knowledge platform for creating a queryable RAG, autonomous reasoning agent, and self-maintaining Wiki.
deep-searcher
Open Source Deep Research Alternative to Reason and Search on Private Data.

Stars

WeKnora
20k
deep-searcher
8.1k

Forks

WeKnora
2.9k
deep-searcher
775

Open issues

WeKnora
556
deep-searcher
53

Language

WeKnora
Go
deep-searcher
Python

Adopt for

WeKnora
WeKnora is an open-source LLM knowledge platform that transforms raw documents into a queryable RAG, autonomous reasoning agent, and self-maintaining Wiki. It is built in Go and offers flexibility through its Docker Com포
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

WeKnora
-
deep-searcher
-

Runtime

WeKnora
-
deep-searcher
-

License

WeKnora
Other
deep-searcher
Apache-2.0

Last pushed

WeKnora
Aug 16, 2026
deep-searcher
Nov 19, 2025

Categories

WeKnora
AI Agents, Evaluation & Observability, LLM Frameworks, Vector Databases
deep-searcher
AI Agents, LLM Frameworks, Vector Databases

Trust and health

Maintenance

WeKnora
Very active (96%)
deep-searcher
Slowing (36%)

Days since push

WeKnora
2d
deep-searcher
272d

Open issues (now)

WeKnora
556
deep-searcher
53

Stars delta

WeKnora
+1.5k (30d)
deep-searcher
+59 (30d)

Open issues delta

WeKnora
+145 (30d)
deep-searcher
0 (30d)

OSV dependency advisories

WeKnora
No published findings from this source as of 2026-07-11
deep-searcher
No lockfile (source not queried)

Full report

deep-searcher
Trust report

Choose WeKnora if…

  • WeKnora is primarily Go; deep-searcher is Python.
  • License: WeKnora is Other, deep-searcher is Apache-2.0.
  • Pricing: Free and open-source under the MIT license..
  • Tags unique to WeKnora: agentic, ai, chatbot, embeddings.
  • Also covers Evaluation & Observability.
  • Use WeKnora if you prefer the Go (Golang) language ecosystem.

When NOT to use WeKnora

  • Avoid WeKnora if your team's primary expertise is not in Go (Golang).
  • If you require real-time updates that are more seamlessly integrated with external systems, as WeKnora focuses on internal maintenance processes.
  • WeKnora might not be the best fit if your specific needs require proprietary licensing or access to features beyond its MIT License.

Choose deep-searcher if…

  • deep-searcher is primarily Python; WeKnora is Go.
  • License: deep-searcher is Apache-2.0, WeKnora is Other.
  • Tags unique to deep-searcher: agentic-rag, deep-research, llm, vector-database.
  • 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 on cards: WeKnora 20k · deep-searcher 8.1k (synced Aug 18, 2026).

Common questions

What is the difference between WeKnora and deep-searcher?
WeKnora: Open-source LLM knowledge platform for creating a queryable RAG, autonomous reasoning agent, and self-maintaining Wiki.. 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 WeKnora over deep-searcher?
Choose WeKnora over deep-searcher when WeKnora is primarily Go; deep-searcher is Python; License: WeKnora is Other, deep-searcher is Apache-2.0; Pricing: Free and open-source under the MIT license.; Tags unique to WeKnora: agentic, ai, chatbot, embeddings; Also covers Evaluation & Observability; Use WeKnora if you prefer the Go (Golang) language ecosystem.
When should I choose deep-searcher over WeKnora?
Choose deep-searcher over WeKnora when deep-searcher is primarily Python; WeKnora is Go; License: deep-searcher is Apache-2.0, WeKnora is Other; Tags unique to deep-searcher: agentic-rag, deep-research, llm, vector-database; 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 WeKnora?
Avoid WeKnora if your team's primary expertise is not in Go (Golang). If you require real-time updates that are more seamlessly integrated with external systems, as WeKnora focuses on internal maintenance processes. WeKnora might not be the best fit if your specific needs require proprietary licensing or access to features beyond its MIT License.
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 WeKnora or deep-searcher more popular on GitHub?
WeKnora has more GitHub stars (19,992 vs 8,060). Stars measure visibility, not whether either tool fits your constraints.
Are WeKnora and deep-searcher open source?
Yes - both are open-source projects on GitHub (WeKnora: Other, deep-searcher: Apache-2.0).
Where can I find alternatives to WeKnora or deep-searcher?
GraphCanon lists graph-backed alternatives at WeKnora alternatives and deep-searcher alternatives (WeKnora 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, WeKnora or deep-searcher?
WeKnora: Very active. 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 WeKnora and deep-searcher?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: WeKnora trust report; deep-searcher trust report.

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