Comparison

Canopy vs Kotaemon

No clear leader: Kotaemon (47.4) and Canopy (45.4) are within the 5-point margin; treat as a tie. The attribute-by-attribute breakdown below, with a source and date on every value, is the honest way to compare them.

Machine formatsMarkdownJSONGraphQLMarkdown is open. JSON and GraphQL need a free key.
Canopy45
Kotaemon47
Score
vioscaleAI score
Canopy45 / 100high · 76%
Kotaemon47 / 100medium · 55%
Pricing
Free tier
Canopy✓
Kotaemon✓
Model
Price level
Canopyfree
Kotaemonfree
Starting price
Canopy$0.07
Kotaemon–
Transparent
Canopy✗
Kotaemon–
Integrations
Count
Canopy24
Kotaemon9
Adoption
Dependent repos
Canopy0
Kotaemon0
Github stars
Canopy1,034
Kotaemon25,797
Activity
Commits last 30d
Canopy0
Kotaemon0
Release
Cadence days
Canopy3
Kotaemon5
History
Canopy13 items
Kotaemon20 items
License
Spdx
KotaemonApache-2.0
Language
Primary
CanopyPython
KotaemonPython
Market
Availability
Content
Faq
Canopy6 items
Kotaemon5 items

Capabilities

Feature-by-feature on the axes that matter for rag tools. “-” means undocumented, not absent.

Capabilities
Hybrid retrieval
Canopy✓
Kotaemon✓
Reranking integration
Canopy✓
Kotaemon✓
Multi hop agentic retrieval
Canopy-
Kotaemon✓
Embedding provider agnostic
Canopy✓
Kotaemon✓
LLM provider agnostic
Canopy✓
Kotaemon✓
Built in rag eval metrics
Canopy✓
Kotaemon-
Citation attribution
Canopy✓
Kotaemon✓
Multimodal rag
Canopy-
Kotaemon✓
Managed ingestion pipeline
Canopy✓
Kotaemon✓
Open source
Canopy✓
Kotaemon✓

What each one is

The product in its own terms, so the numbers below have context.

Canopy

Canopy is an open-source framework that simplifies building RAG applications by handling chunking, embedding, vector storage, chat history, and context retrieval. It provides a CLI tool to interactively evaluate your RAG workflows against non-RAG responses.

Independently observed

Kotaemon

A RAG platform designed for both end users performing document analysis and developers building custom AI-powered QA systems. Offers a web-based interface with support for multiple LLMs, embedding models, and document formats.

Independently observed

Pricing

List pricing as published by each vendor, with the date we read it. Always verify at the source before you buy.

Canopy

from $0.07/GBHybridFree tier

Free tier available. Usage-based Codespaces pricing starting at $0.18/hour compute and $0.07/GB storage. Enterprise plans available.

  • FreeFree
    • Public repositories
    • 2000 CI/CD minutes per month
    • Pull request collaboration
    • Project wiki
    • Dependabot vulnerability alerts
  • Codespaces$0.18 per hour + $0.07 per GB
  • Enterprise CloudContact sales
as of verify ↗

Kotaemon

Open sourceFree tier
as of verify ↗

Platform & deployment

Where each product runs and how it can be hosted. A dash means undocumented, not unsupported.

Platforms
Web
Canopy✗
Kotaemon✓
CLI
Canopy✓
Kotaemon✗
Deployment
Cloud / SaaS
Canopy✓
Kotaemon✗
Self-hosted
Canopy✓
Kotaemon✓

Integrations

What each product connects to. Counts come from the vendor's own integration directory where one exists.

In common (3)
  • OpenAI
  • Cohere
  • Azure OpenAI

Canopy

34 total - 31 not shared
  • Pinecone
  • Qdrant
  • OctoAI
  • Anyscale
  • Google Cloud Run
  • CircleCI
  • Azure Pipelines
  • Codemagic
  • Render
  • CodeRabbit
  • Linear
  • PullRequest
  • Zenhub
  • Zube
  • Codecov
  • Codacy
  • CodeFactor
  • DeepScan
  • GuardRails
  • Coveralls
  • Rollbar
  • Mergify
  • Imgbot
  • WakaTime
  • +7 more
Independently observed

Kotaemon

11 total - 7 not shared
  • Ollama
  • Groq
  • VoyageAI
  • Docling
  • Gradio
  • LanceDB
  • GraphRAG
Independently observed
Still deciding?

Canopy or Kotaemon: which one depends on you

A composite score cannot know your constraints. Describe them and both get re-weighted against what you actually need, with the evidence behind every position.

Free to run, no account needed to start. How the evaluation works

Comparison generated from independently-sourced facts. Every value links to its source and retrieval date. See the method.