# Activepieces vs Jinba Flow

Activepieces records 258,553 monthly visits with +1.5% month-over-month growth and Freemium pricing. Jinba Flow records 14,512 monthly visits with +7.8% growth and Freemium, Contact for Pricing pricing.

| Metric | [Activepieces](https://openaitools.app/tool/activepieces) | [Jinba Flow](https://openaitools.app/tool/jinba-flow) |
| :--- | :--- | :--- |
| Website URL | https://www.activepieces.com | https://jinba.io |
| Categories | AI Workflow, No-Code&Low-Code, AI Code Assistant, AI Agent | AI Workflow, AI Agent, AI API, No-Code&Low-Code |
| Pricing Model | Freemium | Freemium, Contact for Pricing |
| Monthly Visits | 258,553 | 14,512 |
| MoM Growth Rate | +1.5% | +7.8% |
| Primary Market | United States | United States |
| Direct Visits | 111,328 | 3,254 |
| Review Score | 4.6 | 4.3 |
| Saved Count | 0 | 1 |
| Supported Platforms | Website | Website |

## Activepieces

Activepieces is an AI-first automation platform built around the idea that a team's agents and its people should share one workspace. At the center are AI agents: you describe a job in plain words and the agent works out the steps, the order and which tools to open across your connected apps and any MCP server you point it at. Sensitive steps can be gated behind human approval, so money, customer and production actions stay under control.

Underneath the agent layer sits a mature workflow engine with a visual builder. Chat can draft most of a flow, while branching, retries, waitpoints, subflows, error handling and human approvals handle the hard cases. Where a step needs real logic, you can drop into inline TypeScript and keep the rest visual. Chat, Tables (a lightweight structured data layer), a knowledge base and an MCP server round out the platform so agents and teammates operate on the same data.

The project is open source at its core, with hundreds of contributors maintaining MIT-licensed app pieces, and it deploys flexibly: Activepieces Cloud, your own Docker or Kubernetes infrastructure, or a fully air-gapped install. Enterprise controls include projects and access roles, SSO via Okta or Entra, secret managers such as HashiCorp Vault, audit logs streamed to your SIEM, and bring-your-own AI model keys from Anthropic, OpenAI, AWS Bedrock or Google Gemini.

**Pricing & Plans:** Freemium model: a free plan requiring no credit card lets you start building flows and agents, with paid plans for higher run volumes and enterprise features. Deployment options range from the managed cloud to self-hosted and air-gapped, and open-source users can run the community edition on their own infrastructure.

- **AI agents from plain language:** Describe a task in everyday words and the agent determines the steps, chooses tools from your connected apps and MCP servers, and pauses for approval on sensitive actions.
- **Visual flow builder with inline TypeScript:** Build automations on a canvas with branching, retries, waitpoints, subflows and error handling, then write inline TypeScript for the steps that need real code.
- **770+ open-source app connectors:** Every piece is MIT-licensed and community-built, covering the apps you already run, with an HTTP piece for any REST or GraphQL endpoint with auth and pagination handled.
- **Chat, Tables and knowledge base:** Draft flows by chatting, store structured data in Tables that flows and agents can read and write, and keep internal documents searchable by every agent.
- **Enterprise deployment and governance:** Run on the managed cloud, your Docker/Kubernetes stack or air-gapped, with projects, SSO, role-based access, secret managers, audit logs and bring-your-own AI keys.

**Strengths:** Open-source core with MIT-licensed pieces and a genuinely self-hostable build; Strong blend of AI agents, a visual builder and inline TypeScript; Enterprise-grade controls including SSO, roles, secret managers and audit streaming; Large connector library plus an HTTP piece for anything not covered

**Limitations:** The breadth of agents, tables, flows and MCP features can overwhelm new users; Some advanced enterprise capabilities are reserved for paid and self-managed plans; Self-hosting means you own upgrades, scaling and reliability

[Profile (Markdown)](https://openaitools.app/tool/activepieces.md)

## Jinba Flow

Jinba Flow targets banks, insurers, manufacturers and other regulated organisations whose business teams are stuck waiting on IT backlogs. Instead of writing code, a user describes a workflow in plain language and the platform assembles it. Builders can then open the visual editor to refine logic, or work directly in YAML, while non-technical stakeholders keep to the natural-language view. A built-in test runner executes the flow against real data so problems surface before deployment.

Deployment is the point of difference. Completed workflows can be published as an API or as an MCP server, which means existing agents and internal tools can call them without custom glue code. Because the platform is designed for regulated environments, it bundles SOC 2 Type II compliance, HIPAA and GDPR alignment, end-to-end encryption, SSO, role-based access control, audit logging and organisation-level permissions, and it can run on-premises or in a private cloud with private model hosting on providers such as AWS Bedrock, Azure OpenAI or self-hosted Llama models.

Integration coverage includes more than a hundred pre-built connectors and custom connectors for internal systems, with Slack, HubSpot, Salesforce, Notion, Linear, GitHub, Teams, Dropbox and Gmail among the listed services. Common workflows include loan screening, remittance validation, insurance underwriting and claims processing, legal contract review, quote generation, procurement automation, HR intake and meeting scheduling. Pricing scales with team size and usage; free users get community support, paid plans get priority chat support, and enterprise customers receive dedicated success managers.

**Pricing & Plans:** Jinba Flow uses a freemium model plus custom enterprise pricing that scales with team size and usage. A free account lets you start building flows through chat immediately; paid tiers add priority support and enterprise plans include dedicated success managers and on-premises deployment.

- **Natural-language workflow building:** Describe the automation you want in plain language and Jinba assembles the flow, with a visual editor and YAML available for developers who want finer control.
- **Deploy as API or MCP server:** Publish finished workflows so internal tools and AI agents can call them directly, without custom integration code.
- **Real-time testing and debugging:** A built-in test runner executes workflows against real data, showing step-by-step timings and output previews before you ship.
- **Security and compliance controls:** SOC 2 Type II, HIPAA and GDPR alignment with encryption, SSO, RBAC, audit logging and organisation-level permissions.
- **On-premises and private model hosting:** Run Jinba in your own environment and connect providers such as AWS Bedrock, Azure OpenAI or self-hosted Llama models.

**Strengths:** Non-technical teams can ship production workflows without an IT backlog; Deploys as API or MCP server, making workflows usable by existing agents; Compliance posture built in: SOC 2 Type II, HIPAA, GDPR, SSO, RBAC and audit logs; On-premises and private cloud options with private model hosting

**Limitations:** Enterprise-focused pricing means small teams may find the platform heavier than needed; Custom internal connectors can require engineering work despite the no-code premise; Designed around regulated industries, so the security surface can be more than a casual user needs

[Profile (Markdown)](https://openaitools.app/tool/jinba-flow.md)

## Frequently Asked Questions

### How do Activepieces and Jinba Flow compare in monthly traffic?

Activepieces has 258,553 monthly visits, while Jinba Flow has 14,512. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Activepieces has a month-over-month growth rate of +1.5%; Jinba Flow has +7.8%.

### How does pricing compare?

Activepieces: Freemium. Freemium model: a free plan requiring no credit card lets you start building flows and agents, with paid plans for higher run volumes and enterprise features. Deployment options range from the managed cloud to self-hosted and air-gapped, and open-source users can run the community edition on their own infrastructure. Jinba Flow: Freemium, Contact for Pricing. Jinba Flow uses a freemium model plus custom enterprise pricing that scales with team size and usage. A free account lets you start building flows through chat immediately; paid tiers add priority support and enterprise plans include dedicated success managers and on-premises deployment.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Zapier](https://openaitools.app/tool/zapier-com) | 5,065,248 | +0.4% | Freemium, Free Trial, Paid | Automate work across thousands of apps — no code required | [.md](https://openaitools.app/tool/zapier-com.md) |
| 2 | [n8n](https://openaitools.app/tool/n8n) | 4,522,449 | -7.4% | Freemium | Open-source workflow automation built for AI agents and technical teams | [.md](https://openaitools.app/tool/n8n.md) |
| 3 | [MindStudio](https://openaitools.app/tool/mindstudio) | 1,793,337 | +14.2% | Contact for Pricing | No-code builder for custom AI agents and workflows | [.md](https://openaitools.app/tool/mindstudio.md) |
| 4 | [Dify](https://openaitools.app/tool/dify-ai) | 819,691 | -15% | Freemium | Build, deploy, and govern production-ready agentic AI workflows | [.md](https://openaitools.app/tool/dify-ai.md) |
| 5 | [Gumloop](https://openaitools.app/tool/gumloop) | 379,557 | -21.1% | Freemium, Paid, Contact for Pricing | Build, share, and control AI agents that actually do the work | [.md](https://openaitools.app/tool/gumloop.md) |
| 6 | [Tines](https://openaitools.app/tool/tines) | 273,260 | +24.4% | Freemium, Contact for Pricing | A secure environment where teams build, deploy and govern AI agents, apps and automations | [.md](https://openaitools.app/tool/tines.md) |
| 7 | [Relevance AI](https://openaitools.app/tool/relevance-ai) | 192,083 | -15.5% | Free Trial, Contact for Pricing | No-code AI agents and agent teams for real business workflows | [.md](https://openaitools.app/tool/relevance-ai.md) |
| 8 | [FlowHunt](https://openaitools.app/tool/flowhunt-io) | 186,190 | 0% | Free Trial, Paid | Specializes in building conversational chatbots and agentic pipelines visually, but lacks broad traditional connector depth. | [.md](https://openaitools.app/tool/flowhunt-io.md) |
| 9 | [Coze](https://openaitools.app/tool/coze) | 177,539 | -33.3% | Freemium | Strong multi-channel publishing capabilities for AI agents, but less comprehensive for multi-step backend data pipelines. | [.md](https://openaitools.app/tool/coze.md) |
| 10 | [Sim AI](https://openaitools.app/tool/sim-ai) | 140,953 | +20.6% | Freemium, Paid (per user/month), and Enterprise with custom pricing; self-hosting free under Apache 2.0 | Open-source workspace to build, deploy and govern AI agents | [.md](https://openaitools.app/tool/sim-ai.md) |

---
Source: https://openaitools.app/compare/activepieces-vs-jinba-flow

More Markdown: [Categories](https://openaitools.app/categories.md) · [Traffic rankings](https://openaitools.app/rankings.md) · [llms.txt](https://openaitools.app/llms.txt)