trustgraph-ai/trustgraph

• highreadme#1

  Clarify 'TrustGraph' name to avoid misinterpretation as 'decentralized trust'

  原因：

  当前

  TrustGraph is an agent runtime platform built around context graphs — structured, queryable representations of your domain knowledge that ground every agent query in verified, explainable facts in private deployments with sovereign control.

  复制粘贴的修复

  复制

  TrustGraph is an agent runtime platform (not a decentralized trust or reputation protocol) built around context graphs — structured, queryable representations of your domain knowledge that ground every agent query in verified, explainable facts in private deployments with sovereign control.

  待办完成忽略
• mediumreadme#2

  Emphasize 'explainable AI agents' and 'multi-modal context' in README intro

  原因：

  当前

  TrustGraph is an agent runtime platform built around context graphs — structured, queryable representations of your domain knowledge that ground every agent query in verified, explainable facts in private deployments with sovereign control. The platform is the full stack for agentic systems: context graphs, memory, retrieval, orchestration, and inference for precision-critical agent workloads.

  复制粘贴的修复

  复制

  TrustGraph is an agent runtime platform (not a decentralized trust or reputation protocol) built around context graphs — structured, queryable representations of your domain knowledge that ground every agent query in verified, explainable facts in private deployments with sovereign control. It enables explainable AI agents by managing multi-modal context and memory with a graph database. The platform is the full stack for agentic systems: context graphs, memory, retrieval, orchestration, and inference for precision-critical agent workloads.

  待办完成忽略
• lowcomparison#3

  Add a 'Comparison to Alternatives' section in the README

  原因：

  复制粘贴的修复

  复制

  ## Comparison to Alternatives
  
  TrustGraph differentiates itself from general-purpose graph databases (like Neo4j, Memgraph, ArangoDB) by providing a full-stack agent runtime specifically designed for grounding AI agents in verifiable, multi-modal context graphs, rather than just data storage. Unlike agent frameworks (like LangChain, LlamaIndex) that focus on orchestration, TrustGraph integrates the underlying context graph engine, multi-modal database, and RAG pipelines for precision-critical agent workloads, offering sovereign control and explainable outputs.

  待办完成忽略

本次扫描解析到的品类 GEO 通道：google/gemini-2.5-flash, deepseek/deepseek-v4-flash

• 品类问题

  How to build explainable AI agents using a knowledge graph for context?

  你：未被推荐
  AI 推荐顺序：

  1. LangChain
  2. Neo4j
  3. TerminusDB
  4. LlamaIndex
  5. Apache Jena
  6. Stardog
  7. Pydantic
  8. NetworkX
  9. OpenAI's GPT models
  10. Anthropic's Claude
  11. Llama 3
  12. Hugging Face Transformers
  13. PyTorch Geometric (PyG)
  14. Deep Graph Library (DGL)
  15. Protégé
  16. Drools

  AI 推荐了 16 个替代方案，却始终没点名 trustgraph-ai/trustgraph。这就是要补上的差距。

  查看 AI 完整回答
• 品类问题

  What platform manages agent memory and multi-modal context with a graph database?

  你：未被推荐
  AI 推荐顺序：

  1. Memgraph
  2. Neo4j
  3. ArangoDB
  4. TigerGraph
  5. Amazon Neptune
  6. Grakn (now Vaticle's TypeDB)

  AI 推荐了 6 个替代方案，却始终没点名 trustgraph-ai/trustgraph。这就是要补上的差距。

  查看 AI 完整回答

• Metadata completeness

  pass

• README presence

  pass

• Compared to common alternatives in this category, what is the core differentiator of trustgraph-ai/trustgraph?

  pass
  ✓AI 明确点名了 trustgraph-ai/trustgraph

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？

• If a team adopts trustgraph-ai/trustgraph in production, what risks or prerequisites should they evaluate first?

  pass
  ✓AI 明确点名了 trustgraph-ai/trustgraph

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？

• In one sentence, what problem does the repo trustgraph-ai/trustgraph solve, and who is the primary audience?

  pass
  ✓AI 明确点名了 trustgraph-ai/trustgraph

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？