# Augment Code vs Envole

Augment Code records 326,215 monthly visits with +24.1% month-over-month growth and Freemium, Free Trial, Contact for Pricing pricing. Envole records 690 monthly visits with +174.9% growth and Contact for Pricing pricing.

| Metric | [Augment Code](https://openaitools.app/tool/augment-code) | [Envole](https://openaitools.app/tool/envole) |
| :--- | :--- | :--- |
| Website URL | https://www.augmentcode.com | https://envole.ai |
| Categories | AI Agent, AI Code Assistant, AI Code Generator, AI Developer Tools | AI Agent, AI Workflow, No-Code&Low-Code, AI Chatbot |
| Pricing Model | Freemium, Free Trial, Contact for Pricing | Contact for Pricing |
| Monthly Visits | 326,215 | 690 |
| MoM Growth Rate | +24.1% | +174.9% |
| Primary Market | United States | Italy |
| Direct Visits | 137,070 | 273 |
| Review Score | 4.5 | 4 |
| Saved Count | 0 | 0 |
| Supported Platforms | Website | Website |

## Augment Code

Augment Code is an AI coding platform aimed at engineering organisations rather than individual autocomplete users. Its foundation is the Context Engine, which builds a structured understanding of an existing repository — dependencies, architecture, conventions — so that AI suggestions and generated changes fit the codebase instead of reading like generic boilerplate. The product works inside common IDEs and also in the terminal via a CLI.

The platform's recent focus is Cosmos, an agent orchestration layer for the software development lifecycle. Instead of a single assistant answering prompts, Cosmos runs connected loops: a ticket becomes a reviewed pull request, every new PR gets a first-pass code review, failed CI runs get diagnosed, Dependabot and Snyk alerts get triaged into prioritised issues, and on-call engineers inherit a completed investigation. Each loop hands its outcome to the next, and quality gates pause work for human review rather than shipping automatically.

Agents can be deployed in managed cloud sandboxes, on your own machines for code that cannot leave the building, or a mix of both. Native triggers cover GitHub, GitLab, Slack, Linear, Jira, schedules and typed webhooks, with integrations for CI systems. There is a free tier for individuals to try the assistant, while team and enterprise adoption is quote-based; the company has announced it is joining Harness to push the autonomous SDLC from idea to production.

**Pricing & Plans:** Freemium with a free tier for individual developers to start, plus paid team plans and enterprise/contact-for-pricing options. Enterprise deployment includes self-hosted and hybrid agent execution; exact seat and usage pricing is quoted by sales.

- **Context Engine codebase understanding:** Indexes architecture, dependencies and conventions across large repositories so generated code and reviews match how your team actually writes software.
- **Cosmos agent orchestration:** Runs connected SDLC loops — code review, ticket-to-PR, incident triage, dependency upgrades and security remediation — where each agent hands its result to the next.
- **Human-in-the-loop quality gates:** Work pauses at defined checkpoints so engineers approve plans and consequential actions instead of letting agents ship unreviewed changes.
- **Deploy anywhere:** Execute agents in managed cloud sandboxes, on local machines and dev VMs for sensitive code, or in your own AWS and GCP environments.
- **Expert registry and shared memory:** Choose from shipped agents, fork them, or build your own; corrections and shared knowledge improve future runs for the whole team.

**Strengths:** Deep codebase context means suggestions fit existing architecture and conventions; Loops connect across the SDLC instead of solving one isolated task; Quality gates keep humans in control of consequential changes; Flexible deployment including local and self-hosted execution for sensitive code

**Limitations:** Enterprise pricing is quote-based, which makes budgeting harder before a trial; The full value depends on wiring up integrations and triggers across your toolchain; Small teams and solo developers may find the orchestration layer heavier than needed

[Profile (Markdown)](https://openaitools.app/tool/augment-code.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 Augment Code and Envole compare in monthly traffic?

Augment Code has 326,215 monthly visits, while Envole has 690. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Augment Code has a month-over-month growth rate of +24.1%; Envole has +174.9%.

### How does pricing compare?

Augment Code: Freemium, Free Trial, Contact for Pricing. Freemium with a free tier for individual developers to start, plus paid team plans and enterprise/contact-for-pricing options. Enterprise deployment includes self-hosted and hybrid agent execution; exact seat and usage pricing is quoted by 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 | [Replit](https://openaitools.app/tool/replit) | 10,016,437 | -7.7% | Freemium, Paid | Streamlines cloud-based full-stack app building and deployment from natural language, but less tailored for large legacy enterprise repos. | [.md](https://openaitools.app/tool/replit.md) |
| 3 | [Cursor](https://openaitools.app/tool/cursor-sh) | 4,790,129 | +6.5% | Freemium | Integrates directly into VS Code as a daily coding editor, but lacks enterprise-wide multi-agent SDLC orchestration. | [.md](https://openaitools.app/tool/cursor-sh.md) |
| 4 | [Kiro](https://openaitools.app/tool/kiro) | 3,330,476 | +4.6% | Freemium | Focuses on spec-driven engineering and automated verification from AWS, whereas Augment targets broader multi-agent SDLC automation. | [.md](https://openaitools.app/tool/kiro.md) |
| 5 | [Devin](https://openaitools.app/tool/devin) | 2,549,346 | +1% | Paid | Operates as a fully autonomous software engineer tackling complex tickets independently, whereas Augment focuses on developer-in-the-loop workflows. | [.md](https://openaitools.app/tool/devin.md) |
| 6 | [Command Code](https://openaitools.app/tool/command-code) | 2,358,177 | -12.1% | Freemium, Contact for Pricing | Delivers a terminal-first workflow optimized for open-weight models, but offers less graphical enterprise management tooling. | [.md](https://openaitools.app/tool/command-code.md) |
| 7 | [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) |
| 8 | [Orca](https://openaitools.app/tool/orca) | 1,025,891 | +1% | Free, Open Source, Enterprise on request | Provides an open-source agent development environment running parallel CLI coding agents, but requires manual configuration and setup. | [.md](https://openaitools.app/tool/orca.md) |
| 9 | [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) |
| 10 | [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) |

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Source: https://openaitools.app/compare/augment-code-vs-envole

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