Dots vs LLMStack

Side-by-side comparison · Updated September 2026

 DotsDotsLLMStackLLMStack
DescriptionOpenAI's persistent agents for ongoing work across connected apps, with read-only proactive research and separate approval rules for actions.LLMStack is a source-available builder for AI agents, workflows and chatbots that combine model calls with your own data. Its visual builder can chain multiple models and connect data sources, making it more suitable for assembling an application or process than for simply opening a personal chat app. The project documents deployment on your own infrastructure and points to Promptly as its hosted offering. Supported data inputs include documents, websites and connected sources such as Google Drive and Notion. The builder provides preprocessing and vectorization for retrieval workflows. Apps can be shared publicly or with selected people, and viewer and collaborator permissions control access to shared work. The repository also documents HTTP API access and Slack or Discord triggers. Plan for infrastructure, model-provider usage, credentials and permissions as separate decisions. Installing a self-hosted builder does not make externally hosted models free or keep every data request local. Start with a limited workflow and representative documents, review the generated output, and confirm the permissions required by each connected source before expanding access. Compare AnythingLLM when a document-chat workspace is the main need; LLMStack is oriented toward composing the application and its workflow.
CategoryAI AgentsAI Assistant
RatingNo reviewsNo reviews
PricingPricing unavailableUnknown
Starting PriceN/AN/A
Plans—
  • Self-hosting and hosted access — Compare infrastructure, provider and hosting costs
Use Cases—
  • AI Developers
  • Data Scientists
  • Collaborative Teams
  • Businesses
Tags
Open sourceAI agentsWorkflowsApplicationsData
Features
Persistent assignments on a separate cloud computer
Connected-app context with Activity View to inspect and redirect work
Read-only proactive research; actions follow connected-app rules and approval controls
Visual AI workflow and model-chain builder
Data imports from documents, websites and connected services
Document preprocessing and vectorization
Viewer and collaborator permissions
Self-hosted deployment instructions
Hosted offering through Promptly
HTTP API access for apps and chatbots
Slack and Discord workflow triggers
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