--- title: "NeumAI vs Agent-Reach" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/neumtry-neumai-vs-panniantong-agent-reach" tools: ["neumtry-neumai", "panniantong-agent-reach"] --- # NeumAI vs Agent-Reach *GraphCanon updated Aug 21, 2026* ## 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. [NeumAI](https://neum.ai) reports 867 GitHub stars, 50 forks, and 9 open issues, last pushed Jan 15, 2024. [Agent-Reach](https://github.com/Panniantong/Agent-Reach) has 61k stars, 4.9k forks, and 168 open issues, last pushed Jul 25, 2026. Figures are from public GitHub metadata via [NeumAI's repository](https://github.com/NeumTry/NeumAI) and [Agent-Reach's repository](https://github.com/Panniantong/Agent-Reach). | | [NeumAI](/tools/neumtry-neumai.md) | [Agent-Reach](/tools/panniantong-agent-reach.md) | | --- | --- | --- | | Tagline | Framework to manage creation and synchronization of vector embeddings at large scale | AI Agent for Automated Web and Social Media Data Extraction | | Stars | 867 | 60,828 | | Forks | 50 | 4,921 | | Open issues | 9 | 168 | | Language | Python | Python | | Adopt for | 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 facilitates hands-off web and social media scraping via command line with no API costs for retrieving varied internet content. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | Data & Retrieval, Vector Databases | AI Agents, Data & Retrieval | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [NeumAI](/tools/neumtry-neumai.md) | [Agent-Reach](/tools/panniantong-agent-reach.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 948d | 0d | | Open issues (now) | 9 | 168 | | Stars delta | +3 (30d) | Unknown | | Open issues delta | 0 (30d) | Unknown | | Owner type | Organization | User | | Full report | [trust report](/tools/neumtry-neumai/trust.md) | [trust report](/tools/panniantong-agent-reach/trust.md) | ## Decision facts: NeumAI - **Pricing:** freemium - 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. - **Adopt for:** 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 ## Decision facts: Agent-Reach - **Adopt for:** Agent-Reach facilitates hands-off web and social media scraping via command line with no API costs for retrieving varied internet content. ## Choose when ### 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. ### 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 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 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 ## 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 867). 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](/tools/neumtry-neumai/alternatives) and [Agent-Reach alternatives](/tools/panniantong-agent-reach/alternatives) ([NeumAI markdown twin](/tools/neumtry-neumai/alternatives.md), [Agent-Reach markdown twin](/tools/panniantong-agent-reach/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/neumtry-neumai-vs-panniantong-agent-reach.md) 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](/tools/neumtry-neumai/trust); [Agent-Reach trust report](/tools/panniantong-agent-reach/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=neumtry-neumai`](/api/graphcanon/graph?tool=neumtry-neumai) - 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/_