Last updated: 2026-08-19
LLMStack chains 10+ vector database options into no-code AI agent and RAG workflows, connecting language model providers such as OpenAI and Hugging Face without writing code. Self-host on Kubernetes, Docker, or bare servers, or use Promptly's managed cloud service, an open-source alternative to closed no-code builders.
About LLMStack
LLMStack is an open-source, no-code platform built by Promptly for teams that want to build AI agents and RAG workflows without an engineering team. It abstracts the plumbing of connecting a language model to a data source into a visual canvas, so a business analyst or product manager can wire up a working prototype in the time it would take to brief a developer. The project is open-source under Apache 2.0 for the core and ships as a self-hostable stack (Docker, Kubernetes, or bare servers) alongside Promptly's managed cloud, so teams that need to keep data on-premises are not locked into the vendor's hosting. Team development is supported through role-based access controls with viewer and collaborator roles.
Pricing
Free tier: unlimited development environments, but API calls and production deployments are capped. Pro tier: $50/month, billed monthly, with higher rate limits and unlocked production deployments; annual billing brings a discount. Self-hosting the open-source core costs nothing beyond your own infrastructure. LLM provider API costs (OpenAI, Cohere, etc.) are billed separately by those providers, not by LLMStack.
Key Features
- Multi-Model Integration: Connect OpenAI, Cohere, Stability AI, Hugging Face, and 20+ other LLM providers in a single workflow without vendor lock-in.
- Model Chaining & Workflows: Reduce multi-step agent logic to drag-and-drop blocks on a visual canvas instead of writing sequential API calls by hand.
- Data Integration & RAG: Import PDFs, CSVs, Google Drive, Notion, websites, and audio files. The platform auto-indexes and vectorizes data across 10+ vector database options for retrieval-augmented generation.
- Flexible Deployment Options: Deploy to Promptly's managed cloud or self-host on Kubernetes, Docker, or on-premises infrastructure with full data control.
- API-First Architecture: Export workflows as production-grade HTTP APIs. Integrate with Slack, Discord, Zapier, or custom webhooks for custom business process automation.
- Collaborative Development: Build AI applications with teams using role-based access controls, shared workspaces, and version history for multi-user projects.
Pros
- No-code interface democratizes AI development: business analysts and PMs can build production AI applications without engineering dependencies, reducing time-to-value from months to days.
- Multi-model flexibility eliminates lock-in: switch between OpenAI, open-source Llama, Cohere, or custom models mid-project without rebuilding workflows.
- Self-hosting option provides data privacy: deploy on-premises or private cloud, critical for regulated industries handling sensitive customer data.
Cons
- UI performance degrades with scale: users report canvas lag and slowdown when flows exceed 20 blocks on mid-range laptops, limiting complexity of large workflows.
- Limited out-of-box integrations: native connectors for Slack and basic services, but Notion, Airtable, and other popular tools require custom setup.
- Learning curve for advanced features: basic usage is straightforward, but mastering model chaining, RAG tuning, and custom API development requires documentation study and experimentation.
Data Handling
- Compliance
- GDPR (cloud) · SOC 2 (self-hosted with customer responsibility)
Frequently Asked Questions
What are LLMStack's pricing plans in 2026?
LLMStack's Pro tier is $50/month, billed monthly with a discount on annual plans, and unlocks higher API rate limits plus production deployments. The free tier stays available indefinitely for development. Self-hosting the open-source core is free software, though you cover your own server, database, and vector store costs, and any tokens you burn through OpenAI, Cohere, or another connected provider are billed directly by that provider.
What do you get on LLMStack's free tier?
Unlimited development environments, with caps on API calls and production deployments, so it fits building and testing workflows rather than running them at scale. Self-hosting the open-source core is also free software; the cost there is the servers, database, and vector store it runs on.
What are LLMStack's closest competitors?
LangChain gives more hands-on control over observing, evaluating, and deploying agents than a visual canvas does. n8n is a broader workflow automation platform built for technical teams. Make connects a wide range of everyday business apps at scale rather than chaining LLM calls specifically. LLMStack's own ground is a no-code, self-hostable builder around LLM chaining and RAG.
Is LLMStack better than n8n?
They overlap as workflow automation platforms, but LLMStack is built specifically around chaining language models and retrieval-augmented generation, while n8n automates many kinds of business systems for technical teams. LLMStack ships a managed vector store and RAG pipeline; n8n is not LLM-specific by default. Workflows centered on chaining models against your own data belong in LLMStack, general technical automation in n8n.
How long does it take to get going with LLMStack?
The quickstart runs in an afternoon. Open the free tier at llmstack.ai, or self-host the open-source project from its GitHub repository (trypromptly/LLMStack), then connect a model provider such as OpenAI. Drag a data source, a PDF, a website, or a Google Drive folder, onto the canvas and chain a first model call. Deploying the finished workflow as an HTTP API is one more step.
Top Alternatives
- LangChain: LLMStack offers a no-code visual canvas, while LangChain gives hands-on control over observing, evaluating, and deploying agents.
- n8n: LLMStack is LLM-specific with RAG built in; n8n covers broader workflow automation for technical teams.
- Make: LLMStack self-hosts LLM chaining and RAG, while Make connects a wider range of everyday business apps at scale.
- Zapier: LLMStack runs self-hosted RAG workflows; Zapier brings an 8,000-app integration library instead.
HokAI guides covering LLMStack
- Best AI Agent Builders in 2026: Automate, Build or Self-Host: AI agent builder covers three products in 2026: Lindy and Cassidy automate workflows, Atoms and Emergent build apps, two open-source names have gone quiet.