# Devin vs N71 (tlc.ai)

Devin records 2,549,346 monthly visits with +1% month-over-month growth and Paid pricing. N71 (tlc.ai) records 0 monthly visits with 0% growth and Paid, Contact for Pricing pricing.

| Metric | [Devin](https://openaitools.app/tool/devin) | [N71 (tlc.ai)](https://openaitools.app/tool/n71) |
| :--- | :--- | :--- |
| Website URL | https://devin.ai | https://n71.ai |
| Categories | AI Code Assistant, AI Agent, AI Developer Tools | AI Agent, AI Assistant, AI Knowledge Base, AI Knowledge Management |
| Pricing Model | Paid | Paid, Contact for Pricing |
| Monthly Visits | 2,549,346 | 0 |
| MoM Growth Rate | +1% | 0% |
| Primary Market | United States | Global |
| Direct Visits | 1,386,401 | 0 |
| Review Score | 4.3 | 4.1 |
| Saved Count | 0 | 0 |
| Supported Platforms | website | Website |

## Devin

Devin sits at the agentic end of the AI coding spectrum. Instead of suggesting the next line, it takes a ticket-level goal - "add SAML SSO for enterprise customers" or "investigate this API latency spike" - explores the codebase across repositories, implements changes, runs tests, and explains the resulting pull request in plain language. It maintains a wiki-style map of the codebase so it can navigate unfamiliar services and keep documentation current as the code changes.

A defining feature is that Devin works on its own machine. It provisions Windows, Mac, and Linux virtual machines as needed, builds the project, exercises it in a browser, and can record itself clicking through the feature it just built. Long-running work continues in the cloud when your laptop is closed, and large tasks can be split across parallel agents that Devin coordinates and reports on.

For teams, Devin extends beyond one-off prompts. You can tag @Devin in Slack or Teams so it reads a thread and replies with a PR, set up automations that fix failing tests or patch vulnerable dependencies as they appear, and run security reviews. Pricing is seat-based and enterprise-oriented, with an Ultra tier for heavier autonomous usage, and Cognition has marketed large security-credit programs for enterprises.

**Pricing & Plans:** Paid, enterprise-oriented. Devin is sold on a per-seat subscription with tiered plans (including higher-capacity tiers for heavier autonomous use) plus usage allowances; Cognition also runs credit programs and enterprise agreements. Because plans and credit packages change, check Cognition's official pricing page for current numbers.

- **End-to-end autonomous coding:** Devin plans, writes code, runs tests, and opens pull requests across complex, multi-repository codebases without waiting for line-by-line approval.
- **Its own virtual machines:** Devin provisions Windows, Mac, and Linux VMs, builds and runs the project, and tests in a real browser - even recording itself using the feature it built.
- **Slack, Teams, and alert integration:** Mention @Devin in a thread to delegate a fix, or connect CI, PagerDuty, and issue trackers so it reacts to failures and alerts automatically.
- **Parallel cloud agents:** Delegate a large task and Devin splits it across parallel cloud agents that keep working after you close your laptop, then reports back.
- **Codebase wiki and automations:** Devin maintains a living map of the architecture and supports recurring automations such as dependency upgrades, test fixes, and security scans.

**Strengths:** Handles ticket-level autonomous work rather than only suggesting code completions; Tests in its own browser and VMs, which catches issues that pure code generation misses; Deep workflow integration with Slack, Teams, CI, and alerting tools; Keeps working in parallel cloud agents even when your machine is off

**Limitations:** Premium, seat-based pricing puts it out of reach for casual individual use; Complex or poorly specified tasks still need human review before merging; Maximum value depends on having a well-structured repo and clean test setup

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

## N71 (tlc.ai)

N71 is best understood as an infrastructure play rather than a chat product. The company's core idea is that most applications waste tokens: redundant context, repeated calls, and inefficient prompt patterns all inflate the bill at the model provider. Instead of asking developers to rewrite prompts or migrate to a new model, N71 sits transparently behind the API endpoint, inspects and processes requests, and returns results that satisfy the same quality bar for meaningfully less money.

The product is explicitly model agnostic, so it works across whatever LLM providers an application already uses. According to the company, the layer delivers 30%+ lower model costs, and it publishes benchmark methodology plus documentation so teams can reproduce the comparison with their own requests and quality criteria. The pitch is that you keep your model client, prompts and conversation flow unchanged — tlc handles the processing behind the API.

Access is currently gated: the site is in early access with a waitlist, and an invitation unlocks pricing, usage limits and connection details. Because the product is still pre-general-availability, published dollar pricing is not available yet, and prospective users should join the waitlist to get commercial terms.

**Pricing & Plans:** Early access / waitlist. No public list price yet — an invitation includes pricing, usage limits and connection details. The company claims 30%+ lower model costs versus running the same requests without the layer.

- **Transparent API-side optimization:** Fits behind the model API your application already uses, so you keep your existing model client, prompts and conversation flow with no rewrite.
- **Model agnostic by design:** Works across the LLM providers you already call instead of locking you into a single vendor or model family.
- **Claimed 30%+ cost reduction:** The company reports 30%+ lower model costs and provides documentation and a benchmark methodology so you can verify results with your own requests.
- **Reproducible benchmark methodology:** Published benchmarks explain how savings are calculated, including model calls, processing, checks and retries on both sides of the comparison.
- **Early-access onboarding:** Waitlist invitations include pricing, usage limits and the connection details needed to wire tlc into an existing application.

**Strengths:** Model agnostic — works with the providers you already use; No prompt or application rewrite required; it sits behind the API; Publishes a benchmark methodology so savings claims can be independently checked; Early-access onboarding includes pricing, usage limits and connection details

**Limitations:** Still in early access behind a waitlist, so you cannot self-serve today; No public dollar pricing yet, which makes budgeting harder; Real-world savings depend heavily on how wasteful your existing prompt patterns are

[Profile (Markdown)](https://openaitools.app/tool/n71.md)

## Frequently Asked Questions

### How do Devin and N71 (tlc.ai) compare in monthly traffic?

Devin has 2,549,346 monthly visits, while N71 (tlc.ai) has 0. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Devin has a month-over-month growth rate of +1%; N71 (tlc.ai) has 0%.

### How does pricing compare?

Devin: Paid. Paid, enterprise-oriented. Devin is sold on a per-seat subscription with tiered plans (including higher-capacity tiers for heavier autonomous use) plus usage allowances; Cognition also runs credit programs and enterprise agreements. Because plans and credit packages change, check Cognition's official pricing page for current numbers. N71 (tlc.ai): Paid, Contact for Pricing. Early access / waitlist. No public list price yet — an invitation includes pricing, usage limits and connection details. The company claims 30%+ lower model costs versus running the same requests without the layer.

## 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 | An AI-native code editor providing advanced multi-file code generation and editing, though less fully autonomous end-to-end than Devin. | [.md](https://openaitools.app/tool/cursor.md) |
| 2 | [Manus](https://openaitools.app/tool/manus) | 19,195,779 | -1.7% | Free Trial | A general autonomous agent platform executing multi-step goals and browsers, suitable for broader web and coding workflows. | [.md](https://openaitools.app/tool/manus.md) |
| 3 | [Google Antigravity](https://openaitools.app/tool/google-antigravity) | 16,054,109 | +8.1% | Freemium | Google's agentic development platform running parallel AI coding agents across an IDE and CLI workspace. | [.md](https://openaitools.app/tool/google-antigravity.md) |
| 4 | [Replit](https://openaitools.app/tool/replit) | 10,016,437 | -7.7% | Freemium, Paid | A cloud development platform featuring an AI agent that builds, runs, and deploys full-stack apps automatically. | [.md](https://openaitools.app/tool/replit.md) |
| 5 | [Qoder](https://openaitools.app/tool/qoder) | 5,145,040 | +81.8% | Freemium, Free Trial, Free | An agentic coding platform and IDE plugin that reads entire codebases to execute complex multi-file tasks. | [.md](https://openaitools.app/tool/qoder.md) |
| 6 | [Kiro](https://openaitools.app/tool/kiro) | 3,330,476 | +4.6% | Freemium | An AWS spec-driven AI IDE and agent platform that plans, builds, reviews, and verifies software engineering work. | [.md](https://openaitools.app/tool/kiro.md) |
| 7 | [Command Code](https://openaitools.app/tool/command-code) | 2,358,177 | -12.1% | Freemium, Contact for Pricing | The coding agent that learns your coding taste | [.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 | Run many coding agents in parallel, each in its own worktree | [.md](https://openaitools.app/tool/orca.md) |
| 9 | [Unsloth AI](https://openaitools.app/tool/unsloth-ai) | 887,457 | -17.6% | Free | Open-source, memory-efficient fine-tuning and local model running | [.md](https://openaitools.app/tool/unsloth-ai.md) |
| 10 | [Trae](https://openaitools.app/tool/trae) | 702,366 | -7.8% | Freemium | An AI-powered IDE and coding agent that indexes entire repositories to plan, build, and test software. | [.md](https://openaitools.app/tool/trae.md) |

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Source: https://openaitools.app/compare/devin-vs-n71

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