Agentic AI Comparison:
Agenta vs Stack AI
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Introduction
This report provides a detailed comparison between Stack AI and Agenta, two platforms for building AI agents and workflows. Stack AI is a low-code enterprise platform focused on secure, production-grade deployments, while Agenta is an open-source platform emphasizing developer-friendly experimentation and collaboration.
Overview
Stack AI
Stack AI is a no-code/low-code platform designed for enterprises to build, deploy, and manage AI workflows and agents with drag-and-drop builders, support for multiple LLMs (OpenAI, Anthropic, etc.), over 100 integrations, advanced security (SOC2, GDPR, HIPAA), and production features like analytics, roles, and exportable UIs for chatbots, Slackbots, and APIs.
Agenta
Agenta is an open-source AI agent framework (available on GitHub) for developers to prototype, test, and deploy LLM-powered applications. It offers playgrounds for experimentation, versioning, collaboration tools, and evaluation features, with a focus on flexibility for custom agent development rather than no-code enterprise production.[user-provided URLs]
Metrics Comparison
autonomy
Agenta: 9
As an open-source framework, it provides high autonomy for developers to build fully custom agents with tool calling, state management, and LLM orchestration, offering deeper control for sophisticated autonomous behaviors.[user-provided URLs]
Stack AI: 8
Supports autonomous agents with conversation memory, multi-agent collaboration, advanced routing, if-else logic, and real-time actions via drag-and-drop without coding, enabling complex enterprise workflows.
Agenta edges out for developer-level agent autonomy, while Stack AI excels in no-code autonomous workflows for non-technical teams.
ease of use
Agenta: 7
Developer-oriented with playgrounds and UI for experimentation, but requires coding knowledge for full customization and lacks visual no-code tools for non-technical users.[user-provided URLs]
Stack AI: 9
Visual drag-and-drop builder, pre-built templates, and no-code integrations make it accessible for non-developers in finance, HR, and operations to prototype and deploy quickly.
Stack AI is far easier for non-coders and teams; Agenta suits developers comfortable with code.
flexibility
Agenta: 9
Open-source nature allows unlimited customization, integration with any tools/LLMs via code, evaluation frameworks, and versioning for iterative development.[user-provided URLs]
Stack AI: 9
Model-agnostic (OpenAI, Anthropic, Google, on-prem), 100+ integrations, advanced logic/routing, cloud/hybrid/on-prem deployment, and full UI exports provide enterprise-grade adaptability.
Both highly flexible—Stack AI for no-code enterprise scenarios, Agenta for code-based extensibility.
cost
Agenta: 10
Fully open-source (GitHub), free to self-host and use, with optional cloud hosting; minimal costs beyond infrastructure/LLM usage.[user-provided URLs]
Stack AI: 6
Enterprise SaaS with paid tiers (pricing at stack-ai.com/pricing), potentially higher costs for production features, security, and support, though value for regulated industries.[user-provided URLs]
Agenta wins on cost as open-source; Stack AI justifies premium for managed enterprise capabilities.
popularity
Agenta: 7
Growing open-source community via GitHub and docs; developer-focused traction but less enterprise visibility compared to commercial platforms.[user-provided URLs]
Stack AI: 8
Strong enterprise adoption in regulated sectors (finance, healthcare), featured in comparisons and guides as top production platform; active marketing and comparisons.
Stack AI leads in enterprise popularity; Agenta shows promise in open-source developer ecosystems.
Conclusions
Stack AI is ideal for enterprises needing secure, no-code production agents (higher scores in ease of use, enterprise flexibility), scoring overall ~8/10. Agenta excels for developers seeking free, highly customizable open-source tools (stronger in autonomy and cost), also ~8/10. Choose Stack AI for regulated production use; Agenta for prototyping and self-hosted flexibility.