Comparison
EnterpriseRAG-Bench vs Agent-Reach
Verdict
Pick EnterpriseRAG-Bench when tags unique to EnterpriseRAG-Bench: evaluation, dataset, benchmark, enterprise-search; pick Agent-Reach when tags unique to Agent-Reach: agent-infrastructure, ai-search, bilibili, claude-code.
Markdown twin · EnterpriseRAG-Bench alternatives · Agent-Reach alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | EnterpriseRAG-Bench | Agent-Reach |
|---|---|---|
| Maintenance | Steady (64d since push) As of today · github_public_v1 | Very active (0d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Organization account As of today · github_public_v1 | Not a fork · Personal account As of today · github_public_v1 |
| Security (OSV) | No lockfile As of today · none | No MCP manifest As of today · mcp_manifest |
Tagline
- EnterpriseRAG-Bench
- Dataset and benchmark for RAG on company internal documents.
- Agent-Reach
- Give your AI agent eyes to see the entire internet. Read & search Twitter, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu — one CLI, zero API fees.
Stars
- EnterpriseRAG-Bench
- 454
- Agent-Reach
- 55k
Forks
- EnterpriseRAG-Bench
- 46
- Agent-Reach
- 4.5k
Open issues
- EnterpriseRAG-Bench
- 9
- Agent-Reach
- 144
Language
- EnterpriseRAG-Bench
- -
- Agent-Reach
- Python
Adopt for
- EnterpriseRAG-Bench
- -
- Agent-Reach
- -
Persona
- EnterpriseRAG-Bench
- -
- Agent-Reach
- -
Runtime
- EnterpriseRAG-Bench
- -
- Agent-Reach
- -
License
- EnterpriseRAG-Bench
- MIT
- Agent-Reach
- MIT
Last pushed
- EnterpriseRAG-Bench
- May 8, 2026
- Agent-Reach
- Jul 10, 2026
Categories
- EnterpriseRAG-Bench
- LLM Frameworks, Data & Retrieval, Evaluation & Observability
- Agent-Reach
- LLM Frameworks, AI Agents, Developer Tools
Trust and health
Maintenance
- EnterpriseRAG-Bench
- Steady (60%)
- Agent-Reach
- Very active (96%)
Days since push
- EnterpriseRAG-Bench
- 64d
- Agent-Reach
- 0d
Open issues (now)
- EnterpriseRAG-Bench
- 9
- Agent-Reach
- 144
Owner type
- EnterpriseRAG-Bench
- Organization
- Agent-Reach
- User
Security scan
- EnterpriseRAG-Bench
- No lockfile
- Agent-Reach
- No MCP manifest
Full report
- EnterpriseRAG-Bench
- Trust report
- Agent-Reach
- Trust report
Choose EnterpriseRAG-Bench if…
- Tags unique to EnterpriseRAG-Bench: evaluation, dataset, benchmark, enterprise-search.
- Also covers Data & Retrieval, Evaluation & Observability.
- Leaner open-issue backlog (9).
When NOT to use EnterpriseRAG-Bench
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
- Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough.
- Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers.
Choose Agent-Reach if…
- Tags unique to Agent-Reach: agent-infrastructure, ai-search, bilibili, claude-code.
- Also covers AI Agents, Developer Tools.
- More GitHub stars (55k vs 454) - visibility, not fit.
When NOT to use Agent-Reach
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
- AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism.
- Developer Tools: A gateway is overkill when you're pinned to a single provider and model.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (onyx-dot-app/EnterpriseRAG-Bench) · observed Jul 11, 2026
- GitHub forks (onyx-dot-app/EnterpriseRAG-Bench) · observed Jul 11, 2026
- Last push (onyx-dot-app/EnterpriseRAG-Bench) · observed May 8, 2026
- License file (MIT) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (Panniantong/Agent-Reach) · observed Jul 11, 2026
- GitHub forks (Panniantong/Agent-Reach) · observed Jul 11, 2026
- Last push (Panniantong/Agent-Reach) · observed Jul 10, 2026
- License file (MIT) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: EnterpriseRAG-Bench 454 · Agent-Reach 55k (synced Jul 11, 2026).
Common questions
- What is the difference between EnterpriseRAG-Bench and Agent-Reach?
- EnterpriseRAG-Bench: Dataset and benchmark for RAG on company internal documents.. Agent-Reach: Give your AI agent eyes to see the entire internet. Read & search Twitter, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu — one CLI, zero API fees.. See the comparison table for live GitHub stats and shared categories.
- When should I choose EnterpriseRAG-Bench over Agent-Reach?
- Choose EnterpriseRAG-Bench over Agent-Reach when Tags unique to EnterpriseRAG-Bench: evaluation, dataset, benchmark, enterprise-search; Also covers Data & Retrieval, Evaluation & Observability; Leaner open-issue backlog (9).
- When should I choose Agent-Reach over EnterpriseRAG-Bench?
- Choose Agent-Reach over EnterpriseRAG-Bench when Tags unique to Agent-Reach: agent-infrastructure, ai-search, bilibili, claude-code; Also covers AI Agents, Developer Tools; More GitHub stars (55k vs 454) - visibility, not fit.
- When should I avoid EnterpriseRAG-Bench?
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers.
- When should I avoid Agent-Reach?
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Developer Tools: A gateway is overkill when you're pinned to a single provider and model.
- Is EnterpriseRAG-Bench or Agent-Reach more popular on GitHub?
- Agent-Reach has more GitHub stars (54,715 vs 454). Stars measure visibility, not whether either tool fits your constraints.
- Are EnterpriseRAG-Bench and Agent-Reach open source?
- Yes - both are open-source projects on GitHub (EnterpriseRAG-Bench: MIT, Agent-Reach: MIT).
- Where can I find alternatives to EnterpriseRAG-Bench or Agent-Reach?
- GraphCanon lists graph-backed alternatives at EnterpriseRAG-Bench alternatives and Agent-Reach alternatives (EnterpriseRAG-Bench markdown twin, Agent-Reach 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, EnterpriseRAG-Bench or Agent-Reach?
- EnterpriseRAG-Bench: Steady. Agent-Reach: Very 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 EnterpriseRAG-Bench and Agent-Reach?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: EnterpriseRAG-Bench trust report; Agent-Reach trust report.