Stack AI
No-code platform for building enterprise AI agents, chatbots, and RAG workflows
- Category
- No-code/Low-code
- Pricing
- Free tier available for prototyping; paid plans (Starter, Team) begin around $199/month, with custom Enterprise pricing for larger deployments and self-hosting.
- Best for
- Stack AI is best suited to product, IT, and operations teams at mid-size to large companies that need to ship internal or customer-facing AI agents quickly - think HR bots, support assistants, and document-search tools grounded in company data.
- Official site
- www.stack-ai.com
- Last updated
- August 2026
Stack AI sits in the category of "AI agent builders" or "LLM orchestration platforms," aimed at letting teams build production AI applications - internal assistants, customer-facing chatbots, document Q&A tools, workflow automations - without writing full backend code. The core interface is a visual canvas where users chain together nodes representing LLM calls, retrieval steps, conditional logic, API calls, and data transformations.
A major focus is retrieval-augmented generation: connecting LLMs to a company's own documents, databases, and internal tools so responses are grounded in proprietary data rather than the model's general training. Stack AI provides connectors to common enterprise data sources and supports vector search pipelines under the hood, abstracting away much of the plumbing normally required to stand up a RAG system.
Because its target customers are often mid-size and large organizations (including regulated industries like healthcare, finance, real estate, and government), Stack AI emphasizes enterprise readiness: single sign-on, granular permissions, audit trails, and options for private cloud or on-premise deployment. This differentiates it from more consumer- or prosumer-oriented no-code AI builders.
Stack AI is best suited to product, IT, and operations teams at mid-size to large companies that need to ship internal or customer-facing AI agents quickly - think HR bots, support assistants, and document-search tools grounded in company data. It's also a good fit for agencies and consultancies building AI solutions for multiple enterprise clients. It's overkill for someone who just wants a simple single-purpose chatbot, and too costly for casual individual experimentation.
Key features
Visual Agent Builder
A node-based canvas for composing multi-step AI agents and workflows, chaining LLM calls, tools, and logic without writing code.
RAG Pipelines
Built-in support for uploading or connecting documents and data sources, with automatic chunking, embedding, and retrieval for grounded responses.
Multi-LLM Support
Workflows can call different LLM providers (OpenAI, Anthropic, Google, open-source/self-hosted models) and switch between them per step.
Enterprise Connectors
Pre-built integrations with tools like Slack, Google Workspace, SharePoint, and Salesforce to pull in or act on enterprise data.
Flexible Deployment
Finished agents can be published as REST APIs, embeddable chat widgets, or standalone internal applications.
Enterprise Security & Governance
Includes SSO, role-based permissions, audit logging, and options for VPC or on-premise deployment for regulated environments.
Pricing breakdown
Free
- Limited runs/credits for prototyping
- Core workflow builder access
- Community support
Starter
- Higher usage limits
- More LLM provider options
- Standard integrations
Team
- Collaboration features for multiple builders
- Expanded connector access
- Priority support
Enterprise
- SSO and advanced governance
- On-prem/VPC deployment options
- Dedicated support and SLAs
Pros and cons
Pros
- The visual builder can express genuinely complex agent logic - branching, tool use, multi-step reasoning - that goes well beyond simple chatbot flows.
- Native RAG support removes a significant amount of engineering work normally needed to connect LLMs to private company data.
- Support for multiple LLM providers lets teams pick the best or cheapest model per task rather than being locked into one vendor.
- Enterprise-grade security and deployment options (SSO, on-prem, audit logs) make it viable for regulated industries where data residency matters.
- Deployment flexibility (API, widget, or app) means the same built agent can be reused across multiple channels.
Cons
- Pricing starting near $199/month puts it out of reach for hobbyists, students, or very small teams just experimenting with AI agents.
- Building sophisticated multi-agent systems still requires understanding of concepts like prompt design, retrieval tuning, and tool orchestration, so it's not truly zero-learning-curve.
- Some advanced or highly bespoke integrations may still require custom API calls or code steps within the flow.
- As with most RAG platforms, output quality depends heavily on how well source documents are structured and chunked, which can require iteration.
- Rapid feature releases in the fast-moving AI-agent space mean documentation and UI can shift between visits.
Alternatives to Stack AI
Frequently asked questions
Do I need to know how to code to use Stack AI?
No, the core workflow and agent builder is drag-and-drop, though technical familiarity with concepts like prompts and APIs helps for advanced use cases.
Which LLM providers does Stack AI support?
It supports major providers such as OpenAI, Anthropic, and Google, plus options for open-source or self-hosted models depending on plan.
Can Stack AI connect to our own company documents and databases?
Yes, RAG pipelines let you connect internal documents, databases, and tools so agents answer using your company's own data.
How do we deploy an agent built in Stack AI?
Agents can be published as an API endpoint, an embeddable chat widget, or a standalone internal application.
Is Stack AI suitable for regulated industries?
Yes, enterprise plans include SSO, permissions, audit logging, and options for on-premise or VPC deployment to meet compliance needs.
Is there a free way to try Stack AI?
Yes, a free tier is available with limited usage for prototyping before committing to a paid plan.
Ready to try Stack AI?
Head to the official site to explore pricing and start a free trial where available.
Visit Stack AI →