LLM Orchestration

KAG

Logical form-guided reasoning and retrieval framework for professional domain knowledge bases.

Status
Generally available
Last checked
Checked · Oct 11, 2026
License
Open source
Pricing
Free tier · from $0
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What it is

KAG is a logical form-guided reasoning and retrieval framework based on OpenSPG engine and LLMs, used to build logical reasoning and factual Q&A solutions for professional domain knowledge bases. It overcomes the shortcomings of traditional RAG vector similarity calculation models.

KAG stands out by offering logical form-guided reasoning and retrieval, making it uniquely suited for professional domain knowledge bases over traditional RAG models.

When it fits — and when it doesn’t

A good fit for

  • Developers building domain-specific knowledge bases requiring logical reasoning and factual Q&A capabilities

  • Teams needing to overcome limitations of traditional RAG models in professional domains

Look elsewhere if

  • Projects that require real-time streaming or low-latency retrieval

  • Applications where the overhead of setting up a self-hosted solution is prohibitive

Known weaknesses

Each one links to the public issue, changelog or docs page it came from, where we have one.

  1. 01

    Limited integrations with other tools and platforms

    Documentation highlights integration only with a few specific knowledge bases and LLMs

  2. 02

    Performance issues at scale

    Benchmarking shows significant slowdown when querying large domain-specific knowledge bases

What it does well

  • Logical form-guided reasoning and retrieval

  • Based on OpenSPG engine and LLMs

  • Overcomes shortcomings of traditional RAG models

  • Suitable for professional domain knowledge bases

Pricing

Free tier
YesOpen source — free to use
Paid from
$0
Model
Flat rate
Enterprise plan
No

Pricing not independently confirmed — check the vendor’s page.

Performance benchmarks

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Set up KAG

Setup steps, common gotchas and what to check after 30 days.

Open the setup guide →
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