ENTERED TEXT (1) StackAI has created a no-code AI platform that enables businesses to create their own custom AI agents and automations using the large language model of the largest AI vendors such as OpenAI, Anthropic, Google and Meta. StackAI has focused on making it easier for non-technical teams to use AI at scale by providing a drag and drop user experience for creating AI agents, while also ensuring that all solutions meet enterprise grade security and compliance requirements. StackAI is trusted by over 100 Fortune 500 Companies, Banks, Healthcare Providers, and Institutions like MIT Sloan.
(3) Co-founded by Bernardo Aceituno and Antoni Rosinol, StackAI was launched as an enterprise AI agent platform in the Y Combinator Winter 2023 Batch.
(4) StackAI became one of the first AI Infrastructure startups accepted into the Y Combinator Winter 2023 Batch, which provided the company with early credibility in the rapidly evolving AI infrastructure space.
(5) In March 2023, StackAI raised $16 million in Series A funding led by LifeX Ventures, Lobby Capital and Gradient Ventures, among other investors.
(6) Auto Agents Suite was launched by StackAI, allowing users to create natural language based AI agents for enterprise workflow automation.
Cloud-based with on-premises deployment options
Multi-LLM platform supporting OpenAI GPT models, Anthropic Claude, Google, Meta Llama with agentic workflows and 100+ tool integrations
Technology stack from ZoomInfo; integrations and AI capabilities from official sources
| Service | Cost | Details | Source |
|---|---|---|---|
| Free | $0/month | 500 runs/month, 2 projects, 1 seat, community support on Discord | — |
| Starter | $199/month | 2,000 runs/month, 5 projects, 2 seats, basic KBs and data loaders, 7 day free trial | Official pricing page |
| Team | $899/month | 5,000 runs/month, 15 projects, 5 seats, advanced KBs and data loaders, export code | Official pricing page |
| Enterprise | Custom | Unlimited runs/seats, dedicated infrastructure, solution engineers, on-premise/VPC deployment, SSO, SOC2/HIPAA/GDPR compliance | — |
| Feature | Stack AI | SiteGPT | Vertex AI | Parallel AI |
|---|---|---|---|---|
| Core Functionality | Enterprise AI agents & workflows | Customer service automation | AI agents API & Model Garden | White-label business automation |
| Pricing (starting paid) | $199/mo | $39/mo | $12/mo | $99/mo |
| Free Tier | Yes (500 runs) | No | Yes | Yes |
| Enterprise Features | SSO, VPC, on-prem, compliance | Enterprise plan available | Pay-as-you-go | SSO, on-prem |
| API Availability | Yes (export code Enterprise) | Yes | Yes | Yes |
| Setup Complexity | High (IT resources for Enterprise) | 5-minute deployment | Complex billing | Self-service |
| Compliance Focus | SOC2, HIPAA, GDPR | Enterprise plan | — | Enterprise |
| Support Options | Community (Free), Dedicated (Enterprise) | — | Included in Enterprise | |
| Target Market | Regulated enterprises | Marketing/support teams | General AI | Service agencies |
| Deployment Speed | Weeks for Enterprise | Minutes | — | Self-service |
Enterprise IT in regulated industry with compliance features such as stack AI; Stack AI has stronger security than site GPT but more complicated and custom pricing than site GPT.
Choose Stack AI if you need to build enterprise wide internal workflows and choose SiteGPT if you want to build customer facing chatbots.
Stack AI is more cost effective due to its predictable fixed pricing, no token limit, and no code builder compared to vertex AI’s pay as you go pricing and complex billing. Stack AI will be best for non technical teams, vertex AI will be best for advanced ML model optimization.
Stack AI is more appropriate when building drag and drop enterprise agents, while Vertex AI is more appropriate when developing custom AI models.
Compliance and infrastructure are two main focus areas that differentiate Stack AI from Parallel AI, parallel AI offers white label solutions for agencies at lower price points and easier self service configuration. Stack AI will be best for large organizations, Parallel AI will be best for SMB agencies.
Stack AI is more suitable for regulated enterprises while Parallel AI is more suitable for agency white label reselling.
Stack AI provides REST APIs, custom API tools for any REST endpoint, OpenAPI-based reusable tools, and export APIs to deploy workflows as scalable back-end services. Developers may also execute custom Python code in sandboxed nodes.
Stack AI includes support for SSO with Okta, Azure AD, and Google Workspace, multi-factor authentication, and granular RBAC. Enterprise deployments also provide audit logs and compliance reporting for secure access management.
Stack AI builds upon a strong base of enterprise-grade AI workflow automation that includes 100+ integrations, RAG pipelines, and compliance features. In contrast, Voiceflow is focused on developing conversational AI, which means that Stack AI is better-suited for complex backend integration of AI, whereas Voiceflow provides the best option for voice/chatbot UIs.
Yes, Stack AI has received SOC2, HIPAA, and GDPR compliance certification. The company uses PII detection/redaction, encryption at rest/in transit, and does not train LLMs on end-user data. Additionally, users can deploy on-premises or select from various VPC options and utilize strict LLM guardrails to support their enterprise's security requirements.
Stack AI has integrated more than 100 tools including SharePoint, Salesforce, Workday, Slack, Google Drive, Airtable, Trello, databases (Postgres, Notion), and custom REST APIs. Users can create one-click RAG connections to their internal knowledge bases and connect any LLM.
Users can construct and test workflows using the Canvas drag-and-drop interface that comes with pre-built templates. Users can then deploy these workflows as chatbots, forms, Slack bots, or Export APIs with built-in analytics to monitor workflow performance.
Best suited for companies deploying enterprise/internal tools, Stack AI is less suitable for simple customer-facing chatbots. Some pricing models and/or full enterprise features may require contacting a sales representative; this product prioritizes the complexity of workflow development over generating leads.
Yes, Stack AI provides users with the ability to deploy their solutions both on-premises and within a VPC to meet organizations' data residency requirements. Stack AI also supports cloud-based deployment of their products that are fully compliant with major certifications.
Stack AI is well-positioned to serve as a leading no-code solution for enterprises seeking to develop complex AI work flows, agents, and RAG applications that include advanced security measures and more than 100 integrations. The developer-friendly features of Stack AI allow users to easily transition between visually designing solutions and creating customized code/APIs to further integrate their LLMs into production-ready systems.
Stack AI is the top choice for large-scale enterprise AI workflow automation when compliance and integration are key to success.
Stack AI positions itself as an enterprise level AI Infrastructure with a No-Code Workflow Builder, 100 + Integrations, One Click RAG, Python Nodes and Exported APIs. Enterprise Level Security (SOC2/HIPAA/GDPR; On-Premise) and Governance Features Differentiate It in Regulated Industries. Developer Capabilities Extend Beyond No-Code to Full-Stack API Deployment.
Good - detailed info from official blog, docs, academy, and third-party reviews. No public pricing/SLA specifics; enterprise details require sales contact.
Workflows Can Be Deployed As ChatGPT Style Interfaces, Website Chatbots, Voice/SMS/Slack/Teams Bots, Advanced Forms Or Embeddable APIs. Exportable UI's Allow For Custom Branding And Full Control Over User Access.
One Click RAG Pipelines Automatically Index All Types Of Content Including SharePoint, Confluence, Databases And Internal Docs. Support Auto-Sync (Daily/Weekly/Monthly) With Cited Responses From Any LLM.
Python Sandbox Nodes That Come Preinstalled With Libraries, Custom REST API Calls, OpenAPI Tool Creation And Workflow Export As Scalable Backend APIs With Multi-Language SDKs.
Provides Granular RBAC, SSO (Okta/Entra ID), Automatic Audit Logs, LLM Guardrails, PII Redaction, Admin Approval Workflows To Ensure Compliance And Risk Management.
Supports OpenAI, Anthropic, Google And Local LLMs With Routing, Evaluation Frameworks, Cost Controls And Guardrails For Enterprise Model Management. Text to be rewritten in a more human style:
Stack AI connects Open-AI, Anthropic, Google, Local LLMs, Azure & AWS Bedrock with Model Routing and Guardrails.
Stack AI allows Single Sign On (SSO) integration with Okta, Entra ID, Azure AD & Google Workspace for standardizing Enterprise Authentication.
Stack AI has granular Role-Based Access Control (RBAC) with Permissions, Admin Approval & Access Controls for Secure AI Workflows.
Stack AI enables you to build and orchestrate multiple AI agents for Complex Workflows, Autonomous Actions & Collaboration.
Stack AI’s Visual Builder allows users to create workflows with version control, customizable Prompts & LLM Instructions.
Stack AI enables One-Click RAG Pipelines, Data Processing Nodes & Tool Integrations for Normalization of Data.
Stack AI automatically generates Logs, Token Usage Tracking & Optimizes Redundant Calls.
Stack AI includes Built-In LLM Guardrails, PII Redaction & Model Evaluation Frameworks for Safety.
Stack AI includes Real-Time Performance Monitoring of Your Application including Token Usage and Automatic Logs.
Models (evaluation frameworks, guardrails) to track degradation, and monitor use
PII detection, redaction, and validation in workflows
Audit logs for access, usage, and compliance reporting
Approval workflows for admins, and budget/cost alert notifications
Logs (unified) that record every interaction between inputs, outputs, and AI
Tracking of every model (usage), tool, and integration
Automated audit-ready reports of every action taken with a complete trail of activities.
| Use Case | Department | AI Capabilities Required | Business Value |
|---|---|---|---|
| Knowledge Base Assistants | HR/Support | RAG, Multi-source Retrieval, LLM Response | Faster onboarding, support resolution, resource access |
| Snowflake Data Analysis | Data Analytics | NL-to-SQL, Secure Querying, Visualization | On-demand insights without data teams, shortened decision cycles |
| Enterprise Search & Q&A | Knowledge Management | Semantic Search, Document Processing, Agents | Cross-silo discovery from Google Workspace, SharePoint |
| Process Automation Forms | Operations | Forms, API Tools, Workflow Orchestration | No-code automation with Salesforce, Workday integrations |
| Research AI Agents | Research/Marketing | Web Search APIs, Multi-Agent, Real-time Data | Automated workflows with external intelligence |
| Internal Tool Integration | IT/Engineering | 100+ Connectors, Autonomous Agents, APIs | Real-time actions across Slack, SAP, internal systems |
| Compliance Workflows | Legal/Finance | PII Redaction, Audit Logs, Guardrails | Secure document processing and regulatory adherence |
| Multi-Agent Collaboration | All Departments | Agent Orchestration, Context Memory | Complex task handling across teams |
| Category | Top 3 Metrics | Evaluation Criteria | Weighting |
|---|---|---|---|
| Performance | Latency (ms), Throughput (RPS), Cost/Token (USD) | Test private LLM speed, agent scalability, RAG pipelines; validate with production workloads | 25% |
| Reliability | Uptime (%), Error Rate (%), Guardrail Efficacy | Review audit logs, SLA history, model fallback; test multi-provider routing | 25% |
| Security | SSO/RBAC Implementation, PII Redaction, Encryption | Verify SOC2/HIPAA certs, test access controls, data residency options | 20% |
| Scalability | Concurrent Connections, Horizontal Scaling, Integrations | Load test 100+ connectors, multi-region deploy; confirm VPC/on-prem | 15% |
| Governance | RBAC Granularity, Compliance Logs, Workflow Controls | Audit approval workflows, token tracking, no-data-training policy | 15% |
