Top 11 Relevance.ai Alternatives in 2025

What is Relevance.ai?

Relevance.ai is a low-code platform for building an AI workforce with autonomous AI agents. It helps teams automate tasks like data analysis, sales outreach, and internal research using a drag-and-drop builder, pre-built AI agents, and API key integrations.

While Relevance.ai supports basic automation, it often falls short in enterprise settings when hidden credit costs, limited support, or strict compliance requirements become critical.

If you’re considering a Relevance.ai alternative, this guide highlights 11 AI platforms and shows where each one fits.

1. AgentFlow

AgentFlow is the most enterprise-ready Relevance.ai alternative, designed for regulated workflows in finance and insurance. It allows organizations to deploy pre-configured AI agents with full governance, auditability, and compliance controls, making it ideal for industries handling sensitive data.

Unlike Relevance.ai’s low-code model, AgentFlow comes with six specialized modules: Unstructured AI, Document AI, Conversational AI, Database AI, Decision AI, and Report AI. Each of them is aligned to core finance and insurance workflows. 

AgentFlow enables seamless AI integration with stack environments, combining large language model flexibility with specialized functions like:

• explainability
• granular access permissions
• governance of AI models
• enterprise-grade security features. 

These capabilities create a predictable cost structure for mission-critical deployments.

Supporting hybrid deployments across private cloud or on-premise hosting, AgentFlow gives enterprises full control over their own infrastructure.

The trade-off is that it may require more setup upfront, especially when configuring compliance, governance, or enterprise-grade features.

Key Features

• Role‑based access control, audit trails, and compliance certifications.
• Visual workflow builder + APIs for technical users.
• Multi‑agent collaboration and orchestration with oversight.
• Data source integrations; privacy & data governance.
• Enterprise support and SLA options.

Best For

Regulated industries that need both non‑technical agent building and strong governance (e.g., banking, insurance, financial services, health).

Pros

• Predictable, enterprise-grade security and compliance.
• Strong governance & audit features.
• Purpose-built for regulated workflows
• Flexibility to serve non-tech and tech users alike, while supporting complex tasks and advanced AI capabilities across regulated workflows.

Cons

• Higher initial complexity/onboarding for strict deployments.

Pricing

Custom enterprise pricing, available via multimodal.dev.

2. Beam.ai

Beam.ai is best for teams that want to spin up AI agents and AI workflows quickly with minimal setup. It provides a user-friendly design interface, pre-built agents, and an active community, making it a lightweight Relevance.ai alternative.

The platform emphasizes rapid prototyping over enterprise-grade features such as compliance or advanced security features. Its straightforward pricing and free tier appeal to small teams that don’t need regulated deployment options in finance or insurance.

It stands out with a low learning curve, enabling non-technical users to automate multi-step processes without writing code. Setup is simple with an API key, and its onboarding flow includes a drag-and-drop design for quick wins in workflow automation.

The trade-off is limited support for customized AI agents, compliance, and governance. Without audit trails or priority support, Beam.ai is less suited for enterprise users handling sensitive data or requiring multi-agent orchestration at scale.

Key Features

• Drag‑and‑drop visual workflow builder.
• Pre‑built agents/templates for common tasks (sales, outreach, simple workflows).
• Integrations with popular tools (email, Slack, etc.).

Best For

Marketing teams, early‑stage startups, and small to midsize teams wanting productivity gains without heavy regulatory needs.

Pros

• Speed to value.
• Ease of use for non‑technical users.

Cons

• Limited to enterprises requiring strict data oversight.

Pricing

Offered with a free or low-cost tier, with pricing that scales based on usage or subscription.

3. Lindy

Lindy is an open source alternative to Relevance.ai, designed for users who value privacy and control. It supports self-hosting and full ownership of data sources, making it well-suited for organizations managing sensitive data.

This agent framework appeals to technical users who prefer writing code and configuring agents through APIs. 

It provides deep model tuning and flexibility while reducing vendor lock-in, but it also requires significant expertise and setup compared to no-code platforms.

Key Features

• Self‑hosted deployment options.
• Full API/code support.
• Focus on data ownership.

Best For

Organizations with strong privacy, data sovereignty demands, or internal engineering capacity.

Pros

• Better compliance & control.
• Lower dependency on external providers.

Cons

• Steeper learning curve.

Pricing

Often free, open-source core; paid support or enterprise add‑ons.

4. SmythOS

SmythOS is a strong alternative to Relevance.ai for teams that want visual interface design, modular workflows, and collaborative AI agents. It simplifies mapping multi-step processes across multiple AI agents, making AI workflows easier to manage.

The platform includes collaborative tools such as multiple editors and granular access permissions, making it accessible to business users while still supporting technical users who need more advanced design control.

The disadvantage is that SmythOS lacks some enterprise-grade features like audit logs and compliance. For enterprise users in regulated industries, it may require more setup to meet advanced security features and governance standards.

Key Features

• Visual workflow canvas.
• Team collaboration, shared workspaces.
• Role-based access control for structured team management.

Best For

Mid‑size to large teams with a mix of technical & non‑technical users, where workflow complexity is moderate to high.

Pros

• Easier to map out workflows.
• Smooth collaboration.

Cons

• Might require custom setup for enterprise governance.

Pricing

Subscription‐based, with tiers for team and collaborative usage.

5. Gooey AI

Gooey AI is a simpler alternative to Relevance.ai, designed for plug-and-play AI agents that deliver quick wins in sales outreach, content generation, and marketing teams. It prioritizes speed over building multi-agent systems or complex orchestration.

The platform provides a simplified visual interface and ready-to-use templates, allowing operational teams to automate tasks without writing code. Its pre-built agents function almost like ready-made AI assistants, making it a practical no-code platform for fast adoption.

The trade-off is that Gooey AI lacks strong security features, compliance, and governance. Without audit trails or advanced features, it’s less suitable for enterprise users handling sensitive data or requiring multi-agent workflows.

Key Features

• Pre‑built agents.
• User‑friendly interface.
• Integrations for outreach/content tools.

Best For

Marketing/sales teams; small businesses.

Pros

• Speed and ease.
• Low barrier for non‑tech users.

Cons

• Less control for complex or regulated tasks.

Pricing

Subscription plans with a starter pay-as-you-go tier and enterprise options for larger deployments.

6. Maisa AI

Maisa AI is a Relevance.ai alternative designed for business operations teams that need AI agents to handle repetitive tasks and workflow automation. It focuses on structured processes like invoice handling, internal reporting, data analysis, and data-driven insights.

This no-code platform provides ready-to-use templates and embedded business rules, enabling operational teams to automate tasks efficiently without writing code.

The drawback is limited support for multi-agent orchestration across departments. Maisa AI is less effective for complex workflows or multi-agent collaboration, making it unsuitable for enterprise users who require advanced features.

Key Features

• Templates oriented to ops.
• Low‑code builder.
• Embedded business rules for standardized processes.

Best For

Operations teams, finance back‑office, and internal business process automation.

Pros

• Time saved in repetitive tasks.
• Better for standardization.

Cons

• Less flexibility for very custom workflows.

Pricing

Tiered, free, or low-cost for smaller usage.

7. Lyzr

Lyzr is positioned as a developer-focused framework for building custom AI agents, designed to serve both innovation labs and enterprises in risk-sensitive environments. It delivers an enterprise AI solution with governance features such as audit logs, traceability, and compliance controls, going beyond surface-level automation.

By combining multiple agent workflows with decision verification, Lyzr provides confidence to enterprises in finance and insurance handling sensitive data, while remaining accessible to advanced users who need flexibility in managing compliance systems.

The downside is speed. Compared to lighter no-code platforms, Lyzr can feel heavier to deploy, and teams may face added friction when scaling to advanced workflows or prioritizing rapid prototyping.

Key Features

• Developer toolkit for building customized AI agents.
• Open ecosystem supporting modular composability.
• SDKs for direct code integration.

Best For

Enterprises in regulated industries.

Pros

• Confidence in governance and compliance.
• Flexibility for advanced users to design and manage custom AI agents.

Cons

• Might feel more heavyweight.

Pricing

Premium pricing for enterprise features.

8. CrewAI

CrewAI caters to collaborative teams and can substitute for Relevance.ai in environments requiring multi-role agent workflows. Its AI agent platform focuses on shared dashboards, approvals, and role-based access control.

The platform supports multi-agent collaboration by enabling teams to version, review, and approve AI workflows. These team collaboration features are especially valuable for non-developers who need structure and clarity when working with AI agents.

The trade-off is flexibility. CrewAI offers fewer options for building a bespoke AI agent or supporting advanced integrations with existing systems. For enterprise users handling complex workflows, it may feel limiting compared to platforms like AgentFlow.

Key Features

• Shared workspaces, user roles, and team permissions.
• Template sharing, version control.
• Approval workflows for structured collaboration.

Best For

Teams with mixed tech + non‑tech users.

Pros

• Clarity & oversight.
• Easy adoption for non-technical teams.

Cons

• Might lag in depth vs custom code or specific compliance.

Pricing

Subscription-based pricing with tiers based on team size and collaboration features.

9. LangChain

LangChain is a Relevance.ai alternative designed for technical users, developers, and research teams who want maximum flexibility. It functions as a code-first AI agent platform, supporting self-hosting, where workflows are built by composing custom AI agents and chaining components through APIs.

Unlike no-code platforms such as Relevance.ai, LangChain does not rely on drag-and-drop builders. Instead, it enables deep data integration with diverse sources, allowing teams to fine-tune AI models and design highly tailored AI workflows.

This makes LangChain appealing to advanced users experimenting with multi-agent systems, complex workflows, and specialized use cases, particularly in research environments where cutting-edge AI solutions are required. 

However, the platform demands significant technical skills and knowledge of stack AI infrastructure, and without priority support or a polished interface, it can present challenges for broader adoption compared to platforms like AgentFlow.

Key Features

• Full code / API access.
• Open integration with LLMs, vector stores, and custom tool plugging.
• Supports self-hosting for full data control.

Best For

Engineering teams, AI labs, technical R&D.

Pros

• Max control, no limits from UI constraints.
• Highly adaptable for specialized research use cases.

Cons

• Longer development cycles.

Pricing 

Free and open source, with optional enterprise support and managed services.

10. Kore.ai

Kore.ai is strong for conversational AI, virtual assistants, and scenarios where NLP, dialogues, and customer support are the main focus. It stands out as a Relevance.ai alternative for enterprises prioritizing communication-first AI solutions.

The platform offers mature chatbot tooling with AI solutions such as built-in NLP, voice, and omnichannel support. These advanced features make it well-suited for customer-facing AI workflows and AI assistants that require natural interactions.

Kore.ai’s platform excels at customer support automation, help desk operations, and conversation flows. With strong integrations across chat, voice, and other external tools, it provides team collaboration features that enhance customer engagement.

However, it is less effective for multi-agent orchestration or multi-agent systems used in internal workflows. Unlike platforms designed for complex workflows with multiple agents, it specializes mainly in the conversational domain.

Key Features

• Dialogue builders, chat/NLU capabilities.
• Omni‑channel support (voice, chat, etc.).
• Pre-built virtual assistant templates for faster deployment.

Best For

Customer support / virtual assistant use cases, contact center automation.

Pros

• Rich conversation tools.
• Strong customer support automation capabilities.

Cons

• More limited for broader process automation or complex data workflows.

Pricing 

Enterprise pricing based on usage volume, channels, and support needs.

11. Orby AI

Orby AI is a lightweight Relevance.ai alternative with a simpler feature set and fewer enterprise-grade features. This AI tool is designed for teams that want tasks automated quickly, from marketing operations to basic customer support, without heavy setup or advanced infrastructure.

This AI platform is cost-effective for early-stage users. Startups exploring AI capabilities benefit from its free plan, start plan, and basic support for AI workflows.

The downside is scalability. Orby AI lacks strong governance, advanced security features, and multi-agent orchestration. For enterprise users managing sensitive data or complex workflows, it may not deliver the reliability of platforms like AgentFlow.

Key Features

• Simple agent builder; pre‑built templates.
• Free and starter plans for early-stage teams.
• Basic support for AI workflows without heavy setup.

Best For

Startups, small teams, proof‑of‑concepts.

Pros

• Affordable; easy to try.
• Fast adoption for quick experimentation.

Cons

• May outgrow it quickly if workflows or scale needs grow.

Pricing 

Free plan available, with low-cost tiers for expanded features and workflows.

Conclusion

If you need an AI agent platform for regulated industries like finance, insurance, or healthcare, AgentFlow is the top Relevance.ai alternative.

It delivers enterprise-grade features such as role-based access control, advanced security features, auditability, and deployment on your own infrastructure to safeguard sensitive data.

If your priority is speed, a free plan, or fast experimentation, other AI platforms may work. But you’ll likely face limits in multi-agent orchestration, weaker AI integration, hidden costs from credit usage, or fewer options for advanced workflows and multi-agent collaboration.

When assessing Relevance.ai alternatives, ask:

• Does the AI tool meet compliance standards with strong security features?
• Can it support multi-agent systems and secure data sources?
• How much technical knowledge or writing code is required?
• Is the cost structure clear across paid plans?
• Does it integrate with your existing tools to truly enhance productivity?

Book a Meeting With Our Team

AgentFlow is purpose-built for the most complex, regulated workflows in finance and insurance — from loan origination and underwriting to claims processing and compliance reporting.

Unlike Relevance.ai’s low-code platform, AgentFlow’s six specialized agents capture the full context of your processes and deliver automation that is explainable, auditable, and trustworthy.

Want to see how this works in practice? Book a demo today, and discover how leading banks and insurers use AgentFlow to reduce risk, accelerate cycle times, and safeguard sensitive data.

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