# Augment Code vs Supernova.io

Augment Code records 326,215 monthly visits with +24.1% month-over-month growth and Freemium, Free Trial, Contact for Pricing pricing. Supernova.io records 64,656 monthly visits with -12.9% growth and Freemium, Paid, Contact for Pricing pricing.

| Metric | [Augment Code](https://openaitools.app/tool/augment-code) | [Supernova.io](https://openaitools.app/tool/supernova-io) |
| :--- | :--- | :--- |
| Website URL | https://www.augmentcode.com | https://www.supernova.io |
| Categories | AI Agent, AI Code Assistant, AI Code Generator, AI Developer Tools | AI Agent, AI Design Assistant, AI Code Generator, AI Writing Assistants |
| Pricing Model | Freemium, Free Trial, Contact for Pricing | Freemium, Paid, Contact for Pricing |
| Monthly Visits | 326,215 | 64,656 |
| MoM Growth Rate | +24.1% | -12.9% |
| Primary Market | United States | United States |
| Direct Visits | 137,070 | 24,019 |
| Review Score | 4.5 | 4.4 |
| 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)

## Supernova.io

Supernova.io holds a product team's design and code data in one place. It pulls design tokens, components and variables from Figma, stories from Storybook and components from the codebase, then keeps them in sync so that designers, engineers and documentation all reference the same values. Component health tracking flags deprecated or orphaned assets, and multi-brand setup lets organizations manage several visual identities under one roof.

Documentation is authored and published directly in the platform, with real-time collaboration, per-page version history, snapshotting and restore. Because documentation is generated from live Figma and code data rather than written by hand, it stays accurate as the system evolves; drift between design and code is detected and surfaced as suggested fixes.

On the delivery side, Supernova creates filtered MCP servers so AI agents such as Cursor, Claude Code or Codex receive only the knowledge relevant to their team rather than the entire system. Pipelines turn design data into code and open pull requests automatically, while adoption and MCP analytics show which tokens and components are actually used, who is querying the system and where adoption is slipping. Pricing is not published on the homepage — teams start free and enterprise plans are arranged through a demo.

**Pricing & Plans:** The platform offers a free starting tier and paid plans, with enterprise pricing available on request via a demo. Specific plan amounts are not published publicly, so check the pricing page or book a demo for current figures.

- **Connected design and code source of truth:** Tokens, Figma variables, components, Storybook stories and codebase components are consolidated into one synced graph, with health tracking for deprecated or orphaned assets.
- **Agentic documentation:** Docs are written from real Figma and code data, with real-time collaboration, page history snapshots and restore, so documentation reflects the system as it actually is.
- **Filtered MCP servers for AI agents:** Serve curated slices of the design system to Cursor, Claude Code, Codex and other agents so they build from the correct tokens and patterns.
- **Code automation and pipelines:** Design data is transformed into CSS, icons, React components, Android assets and Style Dictionary output, and changes open pull requests automatically.
- **Adoption and MCP analytics:** See which tokens and components teams use in code, who queries the system most and where adoption is falling behind, with feedback turned into suggested fixes.

**Strengths:** Unifies design and code data instead of managing them in separate silos; MCP support makes an existing design system usable by modern AI coding agents; Documentation stays in sync because it is generated from live Figma and code data; Adoption analytics reveal which tokens and components are genuinely used in production

**Limitations:** No public pricing on the homepage, so cost requires contacting sales for enterprise tiers; Deepest value comes with a mature design system, making it heavier for very small teams; Setup involves connecting Figma, Storybook and repositories before it pays off

[Profile (Markdown)](https://openaitools.app/tool/supernova-io.md)

## Frequently Asked Questions

### How do Augment Code and Supernova.io compare in monthly traffic?

Augment Code has 326,215 monthly visits, while Supernova.io has 64,656. 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%; Supernova.io has -12.9%.

### 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. Supernova.io: Freemium, Paid, Contact for Pricing. The platform offers a free starting tier and paid plans, with enterprise pricing available on request via a demo. Specific plan amounts are not published publicly, so check the pricing page or book a demo for current figures.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Notion](https://openaitools.app/tool/t) | 173,441,670 | +0.1% | Freemium | The AI workspace where teams and agents get work done together | [.md](https://openaitools.app/tool/t.md) |
| 2 | [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) |
| 3 | [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) |
| 4 | [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) |
| 5 | [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) |
| 6 | [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) |
| 7 | [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) |
| 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 | [Trae](https://openaitools.app/tool/trae) | 702,366 | -7.8% | Freemium | Provides a fast AI-native IDE experience with deep project understanding, but lacks advanced enterprise context engines. | [.md](https://openaitools.app/tool/trae.md) |

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

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