Workflow Automation

LLMStack

No code platform for building custom LLM applications with ease.

Status
UnmaintainedNo commits in 622 days.
Last checked
Checked · Oct 12, 2026
License
Open source
Pricing
Free tier · from $0
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What it is

LLMStack is a no-code platform designed to build large language model-powered applications using your own data. It simplifies the process of creating, deploying and managing AI-driven apps without needing extensive coding skills.

LLMStack stands out as the only no-code platform specifically designed for building custom LLM applications, offering unparalleled ease of use for developers without sacrificing control over data and deployment.

When it fits — and when it doesn’t

A good fit for

  • Teams needing a no-code solution for LLM application development

  • Projects requiring integration of proprietary or sensitive data into AI applications

  • Developers looking to deploy custom models without extensive coding knowledge

Look elsewhere if

  • Applications that require real-time processing and low-latency responses

  • Scenarios where a managed cloud service with automatic scaling is preferred over self-hosting

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 shows only basic integration examples, lacks enterprise-grade connectors

  2. 02

    Small community and slow response to issues

    GitHub repository has low activity with long wait times for bug fixes and feature requests

What it does well

  • No-code interface for building LLM applications

  • Supports custom data integration

  • Self-hosted deployment options

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

How Fast Is It?

Set up LLMStack

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

Open the setup guide →
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LLMStack — tracked on AI Navigator

Markdown

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