Taskade enregistre 539 714 visites mensuelles avec une croissance mensuelle de -9,4 % et un modèle tarifaire Freemium. Team9 enregistre 0 visites mensuelles avec une croissance de -100 % et un modèle tarifaire Freemium.
Taskade is an AI workspace that turns a single prompt into working business apps, complete with AI agents, automations, databases, tasks and docs — no code required.
Team9.ai is a workspace for running a dependable AI agent team: assign real work to role-based agents, track progress on a shared board, and turn repeatable workflows into reusable playbooks.
Taskade is an AI workspace that turns a single prompt into working business apps, complete with AI agents, automations, databases, tasks and docs — no code required.
Prompt-to-app builder (Taskade Genesis)
Describe an app in a sentence and Taskade generates a working, hosted web app — CRM, dashboard, portal, tracker, booking page — with its own database, no servers or setup to manage.
Custom AI agents and agent teams
Give each agent a role, tools, commands and knowledge sources, train it on your files, projects and websites, and group agents into teams so the right one answers or several work together.
Automations with AI steps
Build trigger-based flows that run 10 to 1,000+ times a month depending on plan, include AI and agent steps, and connect to Gmail, Slack, Google Sheets, HubSpot, Stripe and 100+ other services.
Unified projects, docs, notes and mind maps
Tasks, documents, notes, mind maps and databases live in the same workspace as your agents and apps, so the AI reasons over the same context your team works in.
Forces et avantages
+One prompt produces a genuinely working app with hosting and a database included
+AI agents, automations, projects, docs and mind maps all live in the same workspace
+Free tier is usable and 1,000+ ready-made app kits and templates cut setup time to minutes
Questions fréquentes : Taskade vs Team9
Taskade enregistre 539 714 visites mensuelles, tandis que Team9 enregistre 0. Les estimations de trafic décrivent la taille de l'audience, pas la qualité du produit.
+Available on web, iOS, Android, macOS, Windows and Linux with real-time sync
+MCP server, SKILL.md and developer API make it easy to drive from Claude, Cursor or VS Code
+Bring-your-own-key support on paid plans keeps AI costs under your control
Limites
–Free plan has no monthly AI credits, so you must invite people or share to earn some
–Per-plan user seats mean credits and agent limits are shared across the whole workspace
–A credit-based AI system can feel unpredictable if usage spikes
–Best suited to small and mid-sized teams; deep data modelling or strict enterprise governance may outgrow it
–Plan changes are not available in the App Store version
Team9
Team9.ai is a workspace for running a dependable AI agent team: assign real work to role-based agents, track progress on a shared board, and turn repeatable workflows into reusable playbooks.
Role-based agents
Create agents for engineering, growth, support, research, QA and ops, each with an owner, context and a clear lane for what it handles.
Shared execution board
Humans and agents work from one queue, so priorities stay clear and nothing disappears into a chat thread.
Long-running task management
Agents plan, start, inspect, escalate, finish and summarise; when they hit missing context or a risky decision they raise the issue instead of guessing.
Reusable playbooks
Codify instructions, examples, files, tools and decision rules so a workflow written once is reusable by every agent and teammate.
Forces et avantages
+Treats agents as accountable workers with owners, status and a definition of done
+Shared execution board keeps humans and agents on the same queue
+Playbooks turn successful runs into reusable team memory
+Blockers are escalated rather than silently guessed at
+Control room surfaces usage, latency, errors and cost
+Works with leading models and does not force a new operating model
+Free tier plus a low $19/month Pro entry point
Limites
–Pricing model and agent limits may shift while Pro is free during beta
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