# Aptori vs Augment Code

Aptori records 914 monthly visits with -64.4% month-over-month growth and Contact for Pricing pricing. Augment Code records 326,215 monthly visits with +24.1% growth and Freemium, Free Trial, Contact for Pricing pricing.

| Metric | [Aptori](https://openaitools.app/tool/aptori) | [Augment Code](https://openaitools.app/tool/augment-code) |
| :--- | :--- | :--- |
| Website URL | https://aptori.dev | https://www.augmentcode.com |
| Categories | AI Developer Tools, AI Agent, AI Code Assistant | AI Agent, AI Code Assistant, AI Code Generator, AI Developer Tools |
| Pricing Model | Contact for Pricing | Freemium, Free Trial, Contact for Pricing |
| Monthly Visits | 914 | 326,215 |
| MoM Growth Rate | -64.4% | +24.1% |
| Primary Market | Poland | United States |
| Direct Visits | 359 | 137,070 |
| Review Score | 4.3 | 4.5 |
| Saved Count | 1 | 0 |
| Supported Platforms | Website | Website |

## Aptori

Aptori is an autonomous application security platform built for teams that ship software with both humans and AI agents in the loop. Instead of scattering point scanners across the SDLC, Aptori links everything back to an Application Context Graph: code, services, APIs, dependencies, identities, objects, workflows and runtime paths. That shared context is what lets it decide whether a finding is actually reachable and exploitable rather than just technically present.

The platform spans the whole risk lifecycle. On the BUILD side it handles software composition analysis, SBOM and dependency risk, Kubernetes and IaC security, and AI-assisted static analysis of source code. On the VALIDATE side it covers API security testing, business logic testing and semantic runtime validation that proves how applications and APIs really behave. Autonomous penetration testing agents then safely chain requests, change identities and abuse workflows to prove exploitable attack paths, including BOLA and object-level authorization flaws.

From there, Aptori focuses on noise reduction and triage by correlating context, reachability and exploitability, then accelerates remediation with root-cause guidance, Auto Code Fix and automated pull requests. Continuous vulnerability management tracks each issue through prioritization, retesting and verified closure. The same evidence layer supports compliance programs such as SOC 2, PCI DSS and Secure-by-Design mandates including the EU CRA and UK TSA. Pricing is not published publicly and is available on request via a demo.

**Pricing & Plans:** Pricing is not published publicly. Aptori is positioned as an enterprise platform and directs interested teams to book a demo or contact sales for a quote.

- **AI SAST:** Understands source code, control flow, data flow, authorization and business logic, including AI-generated changes.
- **Autonomous penetration testing:** Controlled agents explore applications, chain requests, switch identities and abuse workflows to prove exploitability.
- **Semantic runtime validation:** Validates how applications and APIs actually behave at runtime, distinguishing real exposure from theoretical risk.
- **API and business logic security:** Tests object-level authorization, workflows and business logic to catch flaws like BOLA and IDOR.
- **Auto Code Fix and verification:** Turns validated risk into developer-ready guidance and automated pull requests, then retests to prove closure.

**Strengths:** Unifies SAST, SCA, API security, pentesting and ASPM in one context-aware platform; Runtime validation reduces false positives by proving real exploitability; Automated pull requests and retesting push issues through to verified closure; Compliance evidence is generated continuously rather than as a periodic exercise

**Limitations:** No public pricing, so evaluation requires a sales conversation; The breadth of capabilities means a meaningful onboarding and integration effort; Best value is realized by enterprises with mature SDLC and API estates

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

## 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)

## Frequently Asked Questions

### How do Aptori and Augment Code compare in monthly traffic?

Aptori has 914 monthly visits, while Augment Code has 326,215. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Aptori has a month-over-month growth rate of -64.4%; Augment Code has +24.1%.

### How does pricing compare?

Aptori: Contact for Pricing. Pricing is not published publicly. Aptori is positioned as an enterprise platform and directs interested teams to book a demo or contact sales for a quote. 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.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Cursor](https://openaitools.app/tool/cursor) | 23,297,751 | +8.4% | Freemium | The AI coding agent for building ambitious software | [.md](https://openaitools.app/tool/cursor.md) |
| 2 | [Google Antigravity](https://openaitools.app/tool/google-antigravity) | 16,054,109 | +8.1% | Freemium | Offers powerful parallel agentic workflows and dedicated IDE tools, but with less focus on proprietary enterprise codebase context. | [.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 | [Aikido Security](https://openaitools.app/tool/aikido-security) | 757,491 | +9.6% | Freemium | All-in-one AppSec platform that finds and auto-fixes vulnerabilities | [.md](https://openaitools.app/tool/aikido-security.md) |

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

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