# Dify vs Envole

Dify records 819,691 monthly visits with -15% month-over-month growth and Freemium pricing. Envole records 690 monthly visits with +174.9% growth and Contact for Pricing pricing.

| Metric | [Dify](https://openaitools.app/tool/dify-ai) | [Envole](https://openaitools.app/tool/envole) |
| :--- | :--- | :--- |
| Website URL | https://dify.ai | https://envole.ai |
| Categories | AI App Builder, AI Agent, AI Workflow, AI API | AI Agent, AI Workflow, No-Code&Low-Code, AI Chatbot |
| Pricing Model | Freemium | Contact for Pricing |
| Monthly Visits | 819,691 | 690 |
| MoM Growth Rate | -15% | +174.9% |
| Primary Market | China | Italy |
| Direct Visits | 470,604 | 273 |
| Review Score | 4.8 | 4 |
| Saved Count | 22 | 0 |
| Supported Platforms | Website | Website |

## Dify

Dify pairs a visual canvas with code-level control so both technical and non-technical teams can assemble AI applications and agents. Workflow Studio turns prompt logic into an inspectable execution graph of building blocks: retrieval, branching, tool calls, human-in-the-loop steps, and model calls. Agent builder lets you create agents by chatting or by configuring them directly, then run them as a standalone app, embed them into a website, or reuse them as a node inside a larger workflow.

A major part of the platform is context engineering. The Knowledge Pipeline lets you define repeatable ingestion flows for files, websites, online documents, and cloud drives, handling extraction, cleaning, chunking, indexing, and retrieval testing before a knowledge base is attached to agents or workflows. The Marketplace supplies model providers, tools, data sources, and MCP integrations that teams can install once and then reuse across many apps as approved plugins.

Dify ships in three deployment shapes: Dify Cloud (fully managed SaaS with workspace, logs, and scaling handled for you), Dify Enterprise (self-hosted or VPC deployment with SSO/SAML, RBAC, audit logs, Helm charts for Kubernetes, and enterprise support), and the open-source Community Edition, a source-available single-command Docker deployment with a large GitHub community. Published apps can be delivered as hosted web apps, API endpoints, embeds, or MCP-compatible tools, with logs, feedback, annotations, latency, and usage analytics to keep improving them after launch.

**Pricing & Plans:** Freemium model with a free cloud sandbox and free trial credits, paid Cloud plans that scale with team size, storage, logs, and usage, and a free open-source Community Edition. Dify Enterprise is quoted per deployment via sales.

- **Workflow Studio:** A visual canvas where retrieval, branching, tool calls, human review, and model steps form a visible, testable execution path you can debug and hand off.
- **Agent Builder:** Create agents through chat or manual configuration, give them skills, tools, and knowledge, then ship them as apps, embeds, or reusable nodes inside workflows.
- **Knowledge Pipeline:** Build repeatable ingestion pipelines for documents, sites, and drives, with extraction, cleaning, chunking, indexing, and retrieval testing before you go live.
- **Plugin Marketplace and MCP:** Install model providers, tools, data sources, and MCP integrations once and reuse approved plugins across every app in the workspace.
- **Flexible Deployment and Observability:** Run on managed Cloud, in your VPC, or self-hosted with Docker, and monitor published apps through logs, annotations, feedback, latency, and usage data.

**Strengths:** Combines a visual builder with code-level extensibility in one product; Three deployment options, including a free self-hosted Community Edition; Strong retrieval and knowledge pipeline tooling for RAG applications; Large plugin marketplace plus MCP support reduces integration work

**Limitations:** Self-hosted deployments require real infrastructure and maintenance effort; Complex multi-step workflows take time to learn and tune; Advanced enterprise governance features sit behind a sales-quoted plan

[Profile (Markdown)](https://openaitools.app/tool/dify-ai.md)

## Envole

Envole describes itself as an "AI system of action for agentic software delivery." The core problem it targets is fragmentation: customer intent lives in one tool, requirements in another, designs in a third, and coding agents build from briefs that have already lost the reasoning behind them. Envole instead creates a shared context layer where signals, decisions, artifacts, code, and tests stay connected back to their source.

The workflow runs through three stages. First, capture: meetings, tickets, messages, documents, and diagrams are collected into one living record that preserves what was said and decided. Second, contextualize: Envole surfaces requests, decisions, risks, blockers, and scope changes with source evidence and customer impact, so teams can decide what to build and why. Third, create: approved intent flows into requirements, working prototypes generated from the real product's components, reviewable technical designs, scoped work items, implementation through preferred IDEs and coding agents, tests, and finally feedback that returns to the next cycle.

A traceability layer ties every artifact to its originating customer need, so teams can see what changed, why, and what needs attention. Envole markets itself as scaffolding for the whole lifecycle rather than a single-purpose code assistant, keeping humans in the loop for review and decisions while agents handle execution. Pricing is not published on the site; the product is sold through a book-a-demo motion aimed at B2B teams.

**Pricing & Plans:** Pricing is not published publicly. Envole offers a login plus a "Book a Demo" flow, indicating custom or contact-based enterprise pricing. Check the site for current commercial terms.

- **Shared context layer:** Customer signals, decisions, artifacts, code, and tests remain connected to their source and to each other, so reasoning is never lost between handoffs.
- **Capture from real work:** Meetings, tickets, messages, documents, diagrams, and support conversations are pulled into one living record that preserves what was said and decided.
- **Signal triage with evidence:** Requests, risks, blockers, and scope changes surface with source evidence and customer impact so teams can decide what to build and why.
- **Prototypes from approved requirements:** Working prototypes are generated with AI from approved requirements using the real product and its existing components, before implementation starts.
- **Intent tracing and verification:** Every artifact traces back to the customer need it came from, and implementation is evaluated against approved intent, constraints, and acceptance criteria.

**Strengths:** Connects the full lifecycle from customer intent to shipped code instead of automating one isolated step; Keeps provenance and evidence attached to every decision and artifact, reducing drift and rework; Supports your existing IDEs, repositories, coding agents, and issue trackers rather than replacing them; Multiplayer by design, so product, design, engineering, and QA share one operating model

**Limitations:** No public pricing or self-serve signup, so evaluation requires contacting sales; Value depends on teams adopting the shared context layer broadly, which is an organizational change, not just a tool install

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

## Frequently Asked Questions

### How do Dify and Envole compare in monthly traffic?

Dify has 819,691 monthly visits, while Envole has 690. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Dify has a month-over-month growth rate of -15%; Envole has +174.9%.

### How does pricing compare?

Dify: Freemium. Freemium model with a free cloud sandbox and free trial credits, paid Cloud plans that scale with team size, storage, logs, and usage, and a free open-source Community Edition. Dify Enterprise is quoted per deployment via sales. Envole: Contact for Pricing. Pricing is not published publicly. Envole offers a login plus a "Book a Demo" flow, indicating custom or contact-based enterprise pricing. Check the site for current commercial terms.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Google Antigravity](https://openaitools.app/tool/google-antigravity) | 16,054,109 | +8.1% | Freemium | Google's agent-first development platform for building and shipping software with AI agents | [.md](https://openaitools.app/tool/google-antigravity.md) |
| 2 | [n8n](https://openaitools.app/tool/n8n) | 4,522,449 | -7.4% | Freemium | An open-source automation powerhouse with deep app connectors, though less specialized for native LLM prompt chaining. | [.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 | [KaneAI](https://openaitools.app/tool/kaneai) | 901,340 | +13.2% | Freemium, Paid, Contact for Pricing | GenAI-native end-to-end QA agent that plans, writes and heals tests in plain language | [.md](https://openaitools.app/tool/kaneai.md) |
| 5 | [Open WebUI](https://openaitools.app/tool/open-webui) | 804,534 | -2.8% | Freemium | A self-hosted chat interface for running local LLMs, though lighter on complex visual workflow orchestration. | [.md](https://openaitools.app/tool/open-webui.md) |
| 6 | [LlamaIndex](https://openaitools.app/tool/llamaindex) | 387,910 | +19.9% | Freemium, Contact for Pricing | Provides advanced programmatic frameworks for document parsing and RAG pipelines, but requires coding instead of visual canvases. | [.md](https://openaitools.app/tool/llamaindex.md) |
| 7 | [Augment Code](https://openaitools.app/tool/augment-code) | 326,215 | +24.1% | Freemium, Free Trial, Contact for Pricing | Agent orchestration platform for your whole software development lifecycle | [.md](https://openaitools.app/tool/augment-code.md) |
| 8 | [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) |
| 9 | [Activepieces](https://openaitools.app/tool/activepieces) | 258,553 | +1.5% | Freemium | Open-source AI automation that unifies agents, flows and 770+ app integrations | [.md](https://openaitools.app/tool/activepieces.md) |
| 10 | [Relevance AI](https://openaitools.app/tool/relevance-ai) | 192,083 | -15.5% | Free Trial, Contact for Pricing | Built for scaling multi-agent workforces and B2B task automation, though less focused on open-source RAG pipelines. | [.md](https://openaitools.app/tool/relevance-ai.md) |

---
Source: https://openaitools.app/compare/dify-ai-vs-envole

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