# Dust vs N71 (tlc.ai)

Dust records 547,217 monthly visits with +1.8% month-over-month growth and Contact for Pricing pricing. N71 (tlc.ai) records 0 monthly visits with 0% growth and Paid, Contact for Pricing pricing.

| Metric | [Dust](https://openaitools.app/tool/dust) | [N71 (tlc.ai)](https://openaitools.app/tool/n71) |
| :--- | :--- | :--- |
| Website URL | https://dust.tt | https://n71.ai |
| Categories | AI Assistant, Large Language Models (LLMs), AI Workflow, AI Knowledge Management | AI Agent, AI Assistant, AI Knowledge Base, AI Knowledge Management |
| Pricing Model | Contact for Pricing | Paid, Contact for Pricing |
| Monthly Visits | 547,217 | 0 |
| MoM Growth Rate | +1.8% | 0% |
| Primary Market | France | Global |
| Direct Visits | 456,919 | 0 |
| Review Score | 4.4 | 4.1 |
| Saved Count | 5 | 0 |
| Supported Platforms | Website | Website |

## Dust

Dust positions itself as 'multiplayer AI' for human-agent collaboration. Rather than giving each employee a private chatbot, it lets teams build agents that have shared access to company knowledge, connected tools, conversations and notifications, so work can move back and forth between people and AI. Agents can be reused across departments, and human review stays part of the loop where it matters.

The platform's differentiator is context. According to Dust, most AI tools can retrieve a single Slack message or CRM record, whereas its agents pull context together across Slack, CRM, documents and other company systems to answer with the full picture and then act on it. Over 70 connectors cover messaging, calendars, CRM, file storage, project management, data and finance tools, and agents can reach MCP servers through the same gateway.

Governance is a first-class feature. Dust offers a dual-layer permission model that separates what agents can access from who can use them, SCIM-synced groups, admin-gated overrides, audit logs and analytics for monitoring adoption, usage, cost and ROI. It is SOC 2 Type II certified, offers US or EU data residency and supports single-tenant deployment. Teams can build agents with 20+ frontier and open-source models from OpenAI, Anthropic, Google, Mistral and others, choosing the right model per workflow. The company says more than 3,000 organizations and 300,000+ agents run on the platform.

**Pricing & Plans:** Contact for pricing. Dust offers a free trial after signup, but its plans are oriented toward teams and enterprises with usage-based credits, volume pricing and dedicated support; you need to talk to sales for exact figures.

- **Agents with company context:** Connect 70+ tools including Slack, Notion, Google Drive, GitHub, Salesforce and Zendesk so agents answer with real company knowledge instead of generic guesses.
- **70+ connectors and MCP support:** Reach messaging, CRM, docs, project management, data, finance and MCP servers through one platform, so agents can act across systems rather than just chat.
- **Model flexibility:** Build agents with 20+ frontier and open-source models from OpenAI, Anthropic, Google and Mistral, and pick the best model for each task.
- **AI-native governance:** A dual-layer permission model, SCIM-synced groups, admin-gated overrides, audit logs and usage analytics keep company data locked down while teams move fast.
- **Multiplayer collaboration:** People and agents share context, tools and notifications, so cross-functional workflows run with reusable skills and human review built in.

**Strengths:** Deep context gathering across 70+ enterprise connectors; Strong enterprise governance with permissions, audit logs and SOC 2 Type II; Model-agnostic: choose among 20+ frontier and open-source models; Shared, reusable agents that scale across departments

**Limitations:** Pricing is sales-led, so costs are hard to estimate before a demo; Setting up connectors and permissions takes real admin work; Best value comes with broad rollout, which is a heavier commitment for small teams

[Profile (Markdown)](https://openaitools.app/tool/dust.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 Dust and N71 (tlc.ai) compare in monthly traffic?

Dust has 547,217 monthly visits, while N71 (tlc.ai) has 0. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Dust has a month-over-month growth rate of +1.8%; N71 (tlc.ai) has 0%.

### How does pricing compare?

Dust: Contact for Pricing. Contact for pricing. Dust offers a free trial after signup, but its plans are oriented toward teams and enterprises with usage-based credits, volume pricing and dedicated support; you need to talk to sales for exact figures. 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 | [Notion](https://openaitools.app/tool/t) | 173,441,670 | +0.1% | Freemium | Provides a unified connected workspace for team documents and databases, but lacks Dust's advanced multi-source enterprise knowledge indexing. | [.md](https://openaitools.app/tool/t.md) |
| 2 | [Salesforce Agentforce (formerly Einstein)](https://openaitools.app/tool/salesforce-einstein) | 111,910,743 | +2.2% | Freemium | Integrates deeply with CRM ecosystems to automate enterprise workflows, but is tightly bound to the Salesforce software suite. | [.md](https://openaitools.app/tool/salesforce-einstein.md) |
| 3 | [Glean](https://openaitools.app/tool/glean) | 3,301,875 | +0.1% | Contact for Pricing | Offers robust enterprise-wide permission-aware search and knowledge management, but with less focus on custom multi-model agent workflows. | [.md](https://openaitools.app/tool/glean.md) |
| 4 | [Abacus.AI](https://openaitools.app/tool/abacus-ai) | 3,278,636 | -1.7% | Contact for Pricing | Combines multi-model chat assistants and automated machine learning optimization, but with a heavier focus on data science pipelines. | [.md](https://openaitools.app/tool/abacus-ai.md) |
| 5 | [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) |
| 6 | [Taskade](https://openaitools.app/tool/taskade) | 539,714 | -9.4% | Freemium | Turn one prompt into live business apps, AI agents and automated workflows | [.md](https://openaitools.app/tool/taskade.md) |
| 7 | [Treg](https://openaitools.app/tool/treg) | 452,935 | +223.4% | Freemium | One key for 4,100+ agent tools, pay per call | [.md](https://openaitools.app/tool/treg.md) |
| 8 | [Gumloop](https://openaitools.app/tool/gumloop) | 379,557 | -21.1% | Freemium, Paid, Contact for Pricing | Excels at visual no-code web scraping and data automation pipelines, but lacks Dust's dedicated internal knowledge base architecture. | [.md](https://openaitools.app/tool/gumloop.md) |
| 9 | [Morph](https://openaitools.app/tool/morph-apply-ai-edits-to-files-fast) | 306,961 | +9.5% | Free Trial, Contact for Pricing | Fast Apply and agent-tuned inference for coding agents | [.md](https://openaitools.app/tool/morph-apply-ai-edits-to-files-fast.md) |
| 10 | [Tines](https://openaitools.app/tool/tines) | 273,260 | +24.4% | Freemium, Contact for Pricing | Focuses on secure enterprise workflow automation and security orchestration, but requires more manual setup for custom AI agents. | [.md](https://openaitools.app/tool/tines.md) |

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

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