Enterprise DNAEnterprise DNA

Open Source · RAG

Embedchain

Universal memory layer for AI Agents

Our verdict

Not reviewed yet

We have not reviewed Embedchain yet

No one at Enterprise DNA has checked this listing against its sources. The description comes from public listings gathered automatically. Any fact below shows where it came from and when it was last checked.

How we review records

From the listing

About Embedchain

Embedchain is a Python framework that provides a memory and retrieval layer for AI agents. It abstracts away vector database setup, embedding models, and chunking logic so developers can focus on agent behavior rather than infrastructure. Agents can ingest documents, web pages, and other data sources, then retrieve relevant context during inference.

Best for

Python developers building prototype or early-stage agents that need document retrieval without managing vector infrastructure directly

Use cases

  • Building chatbots that reference custom documents or knowledge bases
  • Creating agents that need persistent memory across conversations
  • Prototyping RAG systems without managing vector DB infrastructure

Notes

57,321 stars on GitHub. Last updated 2026-06-01. Licensed Apache-2.0.

Pros

  • Reduces boilerplate for common agent memory patterns
  • Supports multiple data sources and vector databases out of the box
  • Active community with 57k+ GitHub stars

Cons

  • Python-only, limits use in non-Python stacks
  • Abstraction layer may hide optimization opportunities for production workloads
  • Dependency on external embedding and vector DB services adds operational complexity

Key facts

What we have checked

Latest version
ts-v3.3.1 (released 25 Sept 2026)
Checked GitHub
GitHub stars
66,006
Checked github api via nightly crawl, recovered from git history 20e874270887c1008f860ee0198e461a23c9e438

Each value shows when we last confirmed it and where it came from. Values we have not confirmed are left out, never guessed.

Stars and usage

How Embedchain is growing

GitHub stars

57,321 to 66,006

stars. 12 July 2026 to 26 Sept 2026, 2 readings.

Source: github api via nightly crawl, recovered from git history 20e874270887c1008f860ee0198e461a23c9e438. Checked .

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EpsillaAlternative to thisOpen sourceNamed in the listingNot dated
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LlamaIndexAlternative to thisOpen sourceNamed in the listingNot dated
MemFreeAlternative to thisOpen sourceNamed in the listingNot dated
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Compare

Compare Embedchain side by side

Sources

Where this comes from

  • GitHubOfficial

    Checked · Latest version

  • github api via nightly crawl, recovered from git history 20e874270887c1008f860ee0198e461a23c9e438Registry

    Checked · GitHub stars

A source shows what was published when we checked it. It does not certify security, performance or a working installation. Read our method.

Changelog

What changed

  1. Released ts-v3.3.1

    Source: GitHub

  2. Released 2.2.1

    Source: GitHub

  3. Released deepseek-plugin-v0.3.2

    Source: GitHub

  4. Released pi-agent-v0.3.2

    Source: GitHub

  5. Released openclaw-v1.2.1

    Source: GitHub

  6. Released opencode-v0.4.1

    Source: GitHub

  7. Released ts-v3.3.0

    Source: GitHub

  8. Released 2.2.0

    Source: GitHub

  9. Released openclaw-v1.2.0

    Source: GitHub

  10. Released opencode-v0.4.0

    Source: GitHub

Pairs with

Other entries in the index that connect to this one. Click through to see the chain.

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