# Moxt vs PromptQL

Moxt records 58,084 monthly visits with -38.3% month-over-month growth and Credits-based (workspace free; pay for AI usage) pricing. PromptQL records 46,603 monthly visits with +59.5% growth and Freemium, Contact for Pricing pricing.

| Metric | [Moxt](https://openaitools.app/tool/moxt) | [PromptQL](https://openaitools.app/tool/promptql) |
| :--- | :--- | :--- |
| Website URL | https://moxt.ai | https://promptql.io |
| Categories | AI Agent, AI Assistant, AI Productivity Tools, AI Workflow | AI Agent, AI Knowledge Management, AI Knowledge Base, AI Assistant |
| Pricing Model | Credits-based (workspace free; pay for AI usage) | Freemium, Contact for Pricing |
| Monthly Visits | 58,084 | 46,603 |
| MoM Growth Rate | -38.3% | +59.5% |
| Primary Market | China | India |
| Direct Visits | 44,683 | 21,273 |
| Review Score | 3.9 | 4.2 |
| Saved Count | 0 | 0 |
| Supported Platforms | Website | Website |

## Moxt

Moxt positions itself as the place where a company stops being a group of people who use software and starts being a team of humans and agents working from one shared context. The product bundles four primitives: Workflow, which splits complex jobs across tuned specialist agents so a pipeline can run unattended for days; Agent Board, a Kanban-style view of what each agent has finished, is currently running, and is waiting on you to unblock; MiniApp, a builder for small internal tools backed by real databases that both humans and agents can operate; and an Agent-Native Workspace where Markdown, HTML, CSV and structured files keep agents grounded across sessions.

Rather than presenting a blank chat box, Moxt ships pre-orchestrated starting points. There are ready-made AI teammate roles such as a Social Media Manager, Cold Outreach Rep, Contract Reviewer and Competitor Watcher, plus templates for content production pipelines, product delivery, bug triage and fix, KOL outreach and startup Kanban boards. You can also pick a model per task from a catalog spanning Claude, GPT, Gemini, Qwen, GLM, Kimi, DeepSeek and image models, with the provider's public rates displayed alongside the credit cost.

The pricing philosophy is deliberately seat-free. Workspace access, member invitations, features and even the number of AI teammates are unlimited and free; the company says people cost little to host while AI work does not, so billing is purely consumption-based on AI credits. You buy credit packs (starting around $20 for 10,000 credits, with $1 equal to 100 credits) that never expire, and agent sandbox runtime is currently offered at no charge. This makes Moxt attractive for small teams that expect heavy agent usage but want to avoid per-seat licenses for occasional collaborators.

**Pricing & Plans:** Free workspace with unlimited members, features and AI teammates. AI work is paid with non-expiring credits (from $20 / 10,000 credits; $1 = 100 credits) at rates aligned to each model provider's public pricing. Cloud agent sandbox is free for now; local agents are coming soon.

- **Workflow orchestration:** Split complex work across specialist agents in staged pipelines that run unattended for days, with each stage handled by a tuned role and the key approval gates left to humans.
- **Agent Board:** A board view showing every agent's progress at a glance so you can see what is done, what is running, and what needs a human decision, then jump in to steer without restarting the work.
- **MiniApp builder:** Build internal tools backed by real databases that both people and agents can use, such as KOL trackers, sales dashboards, task boards and product timelines.
- **Agent-native workspace:** A shared memory layer of Markdown, HTML, CSV and structured files that keeps every agent grounded in the same context across sessions.
- **Multi-model access:** Pick any supported large language or image model per task, including Claude, GPT, Gemini, Qwen, GLM, Kimi and DeepSeek, with transparent per-model credit rates.

**Strengths:** No per-seat licensing: workspace, members and AI teammates are all free; Credits never expire and are priced against official model-provider rates; Ready-made agent roles and workflow templates remove the blank-page problem; Shared workspace memory keeps agents in context over long-running projects

**Limitations:** Costs scale with AI usage, so heavy agent pipelines can become expensive; Local agent execution on your own machine was still announced as coming soon; The breadth of primitives (workflows, mini apps, skills, pages) takes time to learn

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

## PromptQL

PromptQL reframes AI assistance as a team sport. Rather than a single person chatting with an assistant, you spin up a bot for a piece of work — a reliability dashboard, a data quality sheet, an API spec, a monthly metrics deck, a delivery board — and invite the colleagues who actually hold the context. When the bot hits a gap, it asks the right person; when it finds an answer, it writes it back into the artifact next to the discussion.

The product's framing is that three people usually know where to look, and the bot checks all three. In its own examples, three people know what the data does not say, what the code does not say, and what the charts do not say. The bot's job is to reach those people, test their theories against the source systems, and keep the shared artifact correct rather than duplicating knowledge into yet another silo.

Technically, PromptQL bots can run continuously, work on an isolated computer with a browser, build their own tools for arbitrary APIs or databases, and create artifacts and apps. The multiplayer layer includes per-user data isolation — a user cannot ask the bot to access another user's data — editable and deletable messages in shared chat, and private bots users can spawn for sensitive work. An automatically maintained knowledge base captures what the team learns so context compounds rather than resets.

PromptQL also publishes detailed positions on shared context architecture, security, enterprise deployment and pricing, and ships an SDK for teams that want to build multiplayer AI agents themselves.

**Pricing & Plans:** Team pricing starts at $40 per paid user per month, with every user starting free and paid seats purchased in $40 increments. Enterprise considerations such as private networking, dedicated VPC and bring-your-own-cloud or bring-your-own-LLM are handled through contact with the team.

- **Bot per artifact:** Spin up a bot for a specific artifact — a dash board, data quality sheet, spec doc, metrics deck or project board — and give it ongoing responsibility.
- **Invite the humans who know:** Invite the teammates who hold the missing knowledge so the bot can ask them directly and fold their answers into the work.
- **Connected data and tooling:** Bots connect to APIs and databases, build their own tools, and run on an isolated computer with a browser when a task needs one.
- **Multiplayer controls:** Every change is logged, messages can be edited, and users cannot ask the bot to reach another user's data — designed for shared team use.
- **Enterprise deployment:** Architecture, security and deployment pages cover scoped permissions, private networking, dedicated VPC and bring-your-own-LLM options.

**Strengths:** Designed around collaborative work rather than single-user chat; Bots can draw on real data sources, APIs and databases instead of only documents; Strong emphasis on permissions, auditability and enterprise deployment options; Published SDK for building multiplayer AI agents on the platform

**Limitations:** Concept takes a mental shift if you are used to single-user AI chat assistants; Full value depends on connecting your data sources and inviting the right collaborators; Pricing is per paid user on top of a free tier, which needs planning for larger teams

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

## Frequently Asked Questions

### How do Moxt and PromptQL compare in monthly traffic?

Moxt has 58,084 monthly visits, while PromptQL has 46,603. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Moxt has a month-over-month growth rate of -38.3%; PromptQL has +59.5%.

### How does pricing compare?

Moxt: Credits-based (workspace free; pay for AI usage). Free workspace with unlimited members, features and AI teammates. AI work is paid with non-expiring credits (from $20 / 10,000 credits; $1 = 100 credits) at rates aligned to each model provider's public pricing. Cloud agent sandbox is free for now; local agents are coming soon. PromptQL: Freemium, Contact for Pricing. Team pricing starts at $40 per paid user per month, with every user starting free and paid seats purchased in $40 increments. Enterprise considerations such as private networking, dedicated VPC and bring-your-own-cloud or bring-your-own-LLM are handled through contact with the team.

## 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 | [Zapier](https://openaitools.app/tool/zapier-com) | 5,065,248 | +0.4% | Freemium, Free Trial, Paid | Automate work across thousands of apps — no code required | [.md](https://openaitools.app/tool/zapier-com.md) |
| 3 | [n8n](https://openaitools.app/tool/n8n) | 4,522,449 | -7.4% | Freemium | Open-source workflow automation built for AI agents and technical teams | [.md](https://openaitools.app/tool/n8n.md) |
| 4 | [TraeWork](https://openaitools.app/tool/traework) | 2,785,249 | -7.8% | Contact for Pricing | ByteDance's AI-native workspace for natural-language task execution | [.md](https://openaitools.app/tool/traework.md) |
| 5 | [WorkBuddy](https://openaitools.app/tool/workbuddy) | 2,341,262 | +43.9% | Freemium | An AI work partner that turns a sentence into finished office deliverables | [.md](https://openaitools.app/tool/workbuddy.md) |
| 6 | [MiniMax Agent](https://openaitools.app/tool/minimax-agent) | 679,573 | +2.8% | Freemium | An AI supercompanion that handles tasks, code and creative work end to end | [.md](https://openaitools.app/tool/minimax-agent.md) |
| 7 | [LobeHub](https://openaitools.app/tool/lobehub) | 654,548 | -25% | Freemium | Put always-on AI agents on your team chat | [.md](https://openaitools.app/tool/lobehub.md) |
| 8 | [Eigent AI](https://openaitools.app/tool/eigent-ai) | 575,703 | +1.4% | Freemium, Free Trial, Contact for Pricing | Open-source desktop AI workforce that runs browser, file, and app tasks for you | [.md](https://openaitools.app/tool/eigent-ai.md) |
| 9 | [Dust](https://openaitools.app/tool/dust) | 547,217 | +1.8% | Contact for Pricing | Multiplayer AI where people and agents work side by side | [.md](https://openaitools.app/tool/dust.md) |
| 10 | [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) |

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Source: https://openaitools.app/compare/moxt-vs-promptql

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