Comparison
NeumAI vs Agent-Reach
Verdict
Pick NeumAI if neumAI stands out in the space of managing large-scale vector embeddings, offering tools tailored for operations such as retrieval-augmented generation (RAG). Users looking to self-host embeddings management with an open; pick Agent-Reach if agent-Reach facilitates hands-off web and social media scraping via command line with no API costs for retrieving varied internet content.
Markdown twin · NeumAI alternatives · Agent-Reach alternatives
GraphCanon updated 3w
vs
Trust & integrity
| Signal | NeumAI | Agent-Reach |
|---|---|---|
| Maintenance | Dormant (917d since push) As of 4w · github_public_v1 | Very active (0d since push) As of 3w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 4w · github_public_v1 | Not a fork · Personal account As of 3w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) 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
- NeumAI
- Framework to manage creation and synchronization of vector embeddings at large scale
- Agent-Reach
- AI Agent for Automated Web and Social Media Data Extraction
Stars
- NeumAI
- 864
- Agent-Reach
- 61k
Forks
- NeumAI
- 50
- Agent-Reach
- 4.9k
Open issues
- NeumAI
- 9
- Agent-Reach
- 168
Language
- NeumAI
- Python
- Agent-Reach
- Python
Adopt for
- NeumAI
- NeumAI stands out in the space of managing large-scale vector embeddings, offering tools tailored for operations such as retrieval-augmented generation (RAG). Users looking to self-host embeddings management with an open
- Agent-Reach
- Agent-Reach facilitates hands-off web and social media scraping via command line with no API costs for retrieving varied internet content.
Persona
- NeumAI
- -
- Agent-Reach
- -
Runtime
- NeumAI
- -
- Agent-Reach
- -
License
- NeumAI
- Apache-2.0
- Agent-Reach
- MIT
Last pushed
- NeumAI
- Jan 15, 2024
- Agent-Reach
- Jul 25, 2026
Categories
- NeumAI
- Data & Retrieval, Vector Databases
- Agent-Reach
- AI Agents, Data & Retrieval
Trust and health
Maintenance
- NeumAI
- Dormant (18%)
- Agent-Reach
- Very active (96%)
Days since push
- NeumAI
- 917d
- Agent-Reach
- 0d
Open issues (now)
- NeumAI
- 9
- Agent-Reach
- 168
Owner type
- NeumAI
- Organization
- Agent-Reach
- User
Full report
- NeumAI
- Trust report
- Agent-Reach
- Trust report
Choose NeumAI if…
- License: NeumAI is Apache-2.0, Agent-Reach is MIT.
- Pricing: Offers an open-source model under the Apache-2.0 license, potentially featuring a free-tier with premium/support options..
- Requirements: Requires Python and compatibility with infrastructure that supports its backend architecture.; Contact their team at founders@tryneum.com for self-hosting..
- Tags unique to NeumAI: ai, data-engineering, database, embeddings.
- Also covers Vector Databases.
- When you require robust and scalable infrastructure specifically designed for creating and synchronizing vector embeddings at scale.
When NOT to use NeumAI
- When your project requires customization beyond what the provided architecture allows, without the support expected from commercial offerings or competitive open-source frameworks.
- If your needs are simpler and don't demand large-scale operations, NeumAI’s capabilities focused on handling vast vector sets may be excessive for smaller projects.
Choose Agent-Reach if…
- License: Agent-Reach is MIT, NeumAI is Apache-2.0.
- Tags unique to Agent-Reach: agent-infrastructure, ai-agent, ai-search, automation.
- Also covers AI Agents.
- When needing to bypass costly API fees for extensive social media platform data extraction
When NOT to use Agent-Reach
- If strict compliance with website scraping policies is critical due to its use of scraping techniques
- When direct interaction through APIs for precision and reliability is preferred over scraping
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (NeumTry/NeumAI) · observed Jul 21, 2026
- GitHub forks (NeumTry/NeumAI) · observed Jul 21, 2026
- Last push (NeumTry/NeumAI) · observed Jan 15, 2024
- License file (Apache-2.0) · observed Jul 21, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (Panniantong/Agent-Reach) · observed Jul 26, 2026
- GitHub forks (Panniantong/Agent-Reach) · observed Jul 26, 2026
- Last push (Panniantong/Agent-Reach) · observed Jul 25, 2026
- License file (MIT) · observed Jul 26, 2026
- Decision facts (enrichment) · observed Jul 15, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: NeumAI 864 · Agent-Reach 61k (synced Jul 21, 2026).
Common questions
- What is the difference between NeumAI and Agent-Reach?
- NeumAI: Framework to manage creation and synchronization of vector embeddings at large scale. Agent-Reach: AI Agent for Automated Web and Social Media Data Extraction. See the comparison table for live GitHub stats and shared categories.
- When should I choose NeumAI over Agent-Reach?
- Choose NeumAI over Agent-Reach when License: NeumAI is Apache-2.0, Agent-Reach is MIT; Pricing: Offers an open-source model under the Apache-2.0 license, potentially featuring a free-tier with premium/support options.; Requirements: Requires Python and compatibility with infrastructure that supports its backend architecture.; Contact their team at founders@tryneum.com for self-hosting.; Tags unique to NeumAI: ai, data-engineering, database, embeddings; Also covers Vector Databases; When you require robust and scalable infrastructure specifically designed for creating and synchronizing vector embeddings at scale.
- When should I choose Agent-Reach over NeumAI?
- Choose Agent-Reach over NeumAI when License: Agent-Reach is MIT, NeumAI is Apache-2.0; Tags unique to Agent-Reach: agent-infrastructure, ai-agent, ai-search, automation; Also covers AI Agents; When needing to bypass costly API fees for extensive social media platform data extraction.
- When should I avoid NeumAI?
- When your project requires customization beyond what the provided architecture allows, without the support expected from commercial offerings or competitive open-source frameworks. If your needs are simpler and don't demand large-scale operations, NeumAI’s capabilities focused on handling vast vector sets may be excessive for smaller projects.
- When should I avoid Agent-Reach?
- If strict compliance with website scraping policies is critical due to its use of scraping techniques When direct interaction through APIs for precision and reliability is preferred over scraping
- Is NeumAI or Agent-Reach more popular on GitHub?
- Agent-Reach has more GitHub stars (60,828 vs 864). Stars measure visibility, not whether either tool fits your constraints.
- Are NeumAI and Agent-Reach open source?
- Yes - both are open-source projects on GitHub (NeumAI: Apache-2.0, Agent-Reach: MIT).
- Where can I find alternatives to NeumAI or Agent-Reach?
- GraphCanon lists graph-backed alternatives at NeumAI alternatives and Agent-Reach alternatives (NeumAI 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, NeumAI or Agent-Reach?
- NeumAI: Dormant. 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 NeumAI and Agent-Reach?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: NeumAI trust report; Agent-Reach trust report.