Lacquer VS Kagent

Let’s have a side-by-side comparison of Lacquer vs Kagent to find out which one is better. This software comparison between Lacquer and Kagent is based on genuine user reviews. Compare software prices, features, support, ease of use, and user reviews to make the best choice between these, and decide whether Lacquer or Kagent fits your business.

Lacquer

Lacquer
Learn More | Visit Site
Lacquer: The open-source AI workflow engine for code-first engineering teams. Automate complex tasks & build GitOps-native AI internal tools.

Kagent

Kagent
Learn More | Visit Site
Open-source tools for DevOps and platform engineers to build, deploy, and run AI-powered solutions in Kubernetes. From intelligent agents to MCP servers.

Lacquer

Launched 2025-06
Pricing Model Free
Starting Price
Tech used
Tag Developer Tools,Workflow Automation,Multi-agent Framework

Kagent

Launched
Pricing Model Free
Starting Price
Tech used
Tag

Lacquer Rank/Visit

Global Rank
Country
Month Visit

Top 5 Countries

Traffic Sources

Kagent Rank/Visit

Global Rank 1383706
Country Vietnam
Month Visit 18241

Top 5 Countries

41.83%
12.6%
10.54%
7.76%
6.79%
Vietnam United States India Poland Germany

Traffic Sources

5.19%
1.08%
0.1%
7.32%
29.02%
57.18%
social paidReferrals mail referrals search direct

Estimated traffic data from Similarweb

What are some alternatives?

When comparing Lacquer and Kagent , you can also consider the following products

Laminar - Laminar: The open-source platform for AI agent developers. Monitor, debug & improve agent performance with real-time observability, powerful evaluations & SQL insights.

Open Agent Kit - Build custom AI agents fast with Open Agent Kit! Open-source, flexible, & deployable anywhere. Connect LLMs & extend with plugins.

Openlayer - Openlayer: Unified AI governance & observability for enterprise ML & GenAI. Ensure trust, security, & compliance; prevent prompt injection & PII leakage. Deploy AI with confidence.

Laminar AI - Laminar is a developer platform that combines orchestration, evaluations, data, and observability to empower AI developers to ship reliable LLM applications 10x faster.

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