# Augment Code vs Thomson Reuters

Augment Code records 326,215 monthly visits with +24.1% month-over-month growth and Freemium, Free Trial, Contact for Pricing pricing. Thomson Reuters records 17,919,413 monthly visits with +5.5% growth and Contact for Pricing pricing.

| Metric | [Augment Code](https://openaitools.app/tool/augment-code) | [Thomson Reuters](https://openaitools.app/tool/thomson-reuters) |
| :--- | :--- | :--- |
| Website URL | https://www.augmentcode.com | https://www.thomsonreuters.com |
| Categories | AI Agent, AI Code Assistant, AI Code Generator, AI Developer Tools | AI Assistant, AI Legal Assistant, AI Accounting, AI Research Tool |
| Pricing Model | Freemium, Free Trial, Contact for Pricing | Contact for Pricing |
| Monthly Visits | 326,215 | 17,919,413 |
| MoM Growth Rate | +24.1% | +5.5% |
| Primary Market | United States | United States |
| Direct Visits | 137,070 | 7,484,900 |
| Review Score | 4.5 | 4.7 |
| Saved Count | 0 | 3 |
| 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)

## Thomson Reuters

Thomson Reuters is one of the largest professional information providers in the world, built around the idea that high-stakes professional decisions need both authoritative source material and software that brings it into the workflow. Its product families span legal (Westlaw, Practical Law, HighQ, Legal Tracker, CoCounsel Legal), tax and accounting (ONESOURCE, CoCounsel Tax, Guided Assurance, SafeSend), and risk and fraud (CLEAR, Fraud Detect). Much of the content behind these tools is produced by in-house editorial teams, including attorney-editors and tax specialists who maintain and annotate the underlying documents.

The company's newer generation of products centers on generative and agentic AI. CoCounsel, for example, is positioned as an assistant that performs research, document analysis and drafting grounded in Westlaw and Practical Law content rather than open-web material, which is intended to reduce hallucination risk in professional settings. On the trade and compliance side, ONESOURCE modules handle classifications, denied-party screening, free trade agreement qualification and e-invoicing reporting for multinational organizations.

Because its customers are firms, corporations and government bodies, Thomson Reuters sells primarily through direct enterprise agreements rather than self-serve checkout. Pricing is quoted per organization and depends on the modules, seats and content subscriptions involved, so this page does not list fixed figures. Prospective buyers typically request a demo or contact sales to scope a contract.

**Pricing & Plans:** No public price list. Thomson Reuters sells enterprise subscriptions and licenses tailored per organization, so costs depend on the selected products, seats and content packages. Pricing is available on request through sales or a product demo.

- **AI legal assistant (CoCounsel):** Research, analyze documents and draft legal work grounded in Westlaw and Practical Law content, with citations back to source material.
- **Westlaw and Practical Law content:** Deep legal research libraries plus attorney-authored guidance, templates and checklists maintained by an in-house editorial team.
- **Tax, audit and accounting software:** ONESOURCE and related tools cover corporate tax determination, indirect compliance, provisioning and audit workflow automation for multi-entity organizations.
- **Global trade and compliance:** Automated HS code classification, denied-party screening against 800+ lists, free trade agreement management and export controls.
- **Risk and fraud intelligence:** Public-records investigation, identity verification, adverse media monitoring and machine-learning fraud detection for compliance and law enforcement teams.

**Strengths:** Backed by decades of curated, editor-maintained source content rather than open-web scraping; Broad coverage across legal, tax, trade and risk in one vendor relationship; AI features are grounded in the company's own verified content, which supports defensible outputs; Enterprise-grade security, integrations and support suited to regulated industries

**Limitations:** Enterprise licensing is expensive and generally out of reach for individuals or very small firms; No transparent self-serve pricing; all quotes go through a sales process; Large product catalog can be complex to navigate and integrate across modules

[Profile (Markdown)](https://openaitools.app/tool/thomson-reuters.md)

## Frequently Asked Questions

### How do Augment Code and Thomson Reuters compare in monthly traffic?

Augment Code has 326,215 monthly visits, while Thomson Reuters has 17,919,413. 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%; Thomson Reuters has +5.5%.

### 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. Thomson Reuters: Contact for Pricing. No public price list. Thomson Reuters sells enterprise subscriptions and licenses tailored per organization, so costs depend on the selected products, seats and content packages. Pricing is available on request through sales or a product demo.

## 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 | 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) |
| 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 | [Harvey](https://openaitools.app/tool/harvey-ai) | 1,832,998 | +26.1% | Contact for Pricing | Advanced generative AI workspace built specifically for elite law firms, but lacks Thomson Reuters' broad tax and regulatory databases. | [.md](https://openaitools.app/tool/harvey-ai.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-thomson-reuters

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