A professional guide to StackAI enterprise agents, agentic RAG, no-code workflows, security and approvals.
Many no-code AI tools are designed for individuals or small teams. StackAI is aimed at a different audience: enterprises that want to build AI agents for internal processes while keeping tight control over data, access, and approvals. It combines a visual workflow builder with enterprise features such as human review steps, model choice, and flexible deployment.
This guide covers what StackAI offers, who it suits best, and how to design reliable agents with it.
StackAI (the company writes its name without a space, though many sources write "Stack AI") is a no-code platform for designing, testing, deploying, and governing AI agents that work across enterprise systems. It was founded in 2022 by MIT alumni Bernardo Aceituno and Antoni Rosinol, and it focuses on back-office and internal workflows rather than public-facing chatbots.
Important news: according to TechCrunch coverage cited by third-party guides, Asana acquired StackAI in May 2026, with plans to fold it into its AI workflow tools. As of the latest reports, StackAI still sells its product on its own website, but check the official site for any changes to branding, pricing, or product direction.
| Capability | What it does |
|---|---|
| Visual workflow builder | A drag-and-drop canvas connecting inputs, documents, knowledge bases, models, logic, code, and actions |
| Agentic RAG | Lets agents retrieve answers from your private documents and data |
| Multiple model providers | Choose from different large language models, depending on cost, quality, and policy |
| Human-in-the-loop controls | Approval gates that pause workflows at sensitive decisions |
| Interfaces | Deploy the same workflow as a chat assistant, form, batch process, or API |
| Enterprise integrations | Connect to business systems and data sources through prebuilt connectors |
| Analytics and evaluation |
| Monitor runs and test agent quality before and after publishing |
StackAI is most often used for internal, document-heavy, and compliance-sensitive work:
StackAI is generally positioned for mid-size and large organizations with security, compliance, or data-residency requirements. It is less compelling for solo users or very small teams that just want a quick personal assistant. Review sites also describe it as better suited to AI engineers and data teams building LLM-powered processes than to customer-facing chatbots.
| Need | Better fit |
|---|---|
| Enterprise internal agents with governance | StackAI |
| Custom agents across sales and operations | Relevance AI |
| Microsoft-centric organizations | Copilot Studio |
| CRM-centric organizations | Salesforce Agentforce |
| Simple app-to-app automation | Zapier or Make |
| Developer-controlled multi-agent code | CrewAI |
Start with a document-heavy, repetitive process, such as answering policy questions or extracting key fields from contracts. Avoid broad, high-risk goals at first.
Clean and organize the documents the agent will use. Remove outdated versions, because retrieval-based agents repeat whatever they find.
Add an input node, connect your document or knowledge-base nodes, add a model node, and then add logic and output nodes. Keep the structure simple at first.
Use this structure for each model step:
Role + Task + Allowed sources + Rules + Output format
Example: "You are a compliance assistant. Answer only from the approved policy documents. Cite the document name for every answer. If the answer is not in the documents, say you cannot find it. Never provide legal advice."
Insert approval gates before sensitive actions, such as sending external communications or updating records of record.
Run realistic questions and documents, including edge cases and misleading inputs. Use evaluation tools to compare outputs across runs and models.
Publish the workflow as a chat assistant, a form, a batch job, or an API, depending on how your team will use it.
Track usage, failures, and answer quality in analytics. Update instructions, knowledge sources, and models as needs change.
StackAI is marketed to enterprises, and third-party reviews describe features such as SSO, audit logs, access controls, private model deployment options, SOC 2 Type II, and on-premise or VPC deployment on enterprise plans. Treat these as claims to verify. Ask the vendor for current documentation, certifications, and data-processing terms before sending sensitive data through any AI platform.
StackAI's pricing has changed. Recent reports describe the official pricing page as listing a limited free tier and a custom-priced Enterprise plan, while older self-serve tiers mentioned on third-party sites were withdrawn. Enterprise plans typically involve custom run and seat allowances, dedicated infrastructure, and support.
Also remember that AI model usage may be billed on top of platform fees. Always confirm current plans on the official StackAI pricing page and request a quote for production use.
StackAI is a strong option for organizations that want to build internal AI agents without writing a full engineering stack, while keeping governance, approvals, and security front and center. Its visual builder, agentic RAG, model flexibility, and human-in-the-loop controls fit document-heavy, compliance-sensitive work well. The trade-offs are enterprise-oriented pricing, a product direction that may evolve after its acquisition by Asana, and less appeal for small teams that only need lightweight automation. If you need personal assistants or quick app-to-app automations, tools like Lindy, Zapier, or Make may be easier. For governed, internal AI workflows at scale, StackAI deserves a close look.
Begin with one well-defined workflow, measure accuracy and time saved, and expand with proper oversight. Explore StackAI and test your first agent.
StackAI is a no-code platform for designing, testing, deploying, and governing AI agents that work across enterprise systems. It uses a visual workflow builder, supports retrieval over private data, and includes human approval controls. Learn more at stackai.com.
StackAI was founded in 2022 by Bernardo Aceituno and Antoni Rosinol. Reports state that Asana acquired StackAI in May 2026, so check the official site for current ownership and product direction.
No. StackAI uses a drag-and-drop canvas, though technical users can add code and API logic for advanced workflows.
Agents can answer questions from private documents, process and extract data from files, route requests, call APIs, and pause for human approval before sensitive actions.
StackAI has offered a limited free tier for evaluation, with custom Enterprise plans for production. Plans change, so check the official pricing page for current details.
StackAI promotes enterprise features such as SSO, audit logs, access controls, and compliance support on higher plans. Verify current certifications and data-handling terms with the vendor before using sensitive data.
StackAI focuses on governed, no-code internal workflows with visual orchestration and human approvals. Relevance AI emphasizes custom multi-agent teams, while Copilot Studio is built around the Microsoft 365 and Power Platform ecosystem.
