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AI delivery for every team

Give repetitive work to an AI agent team while people make the decisions and approvals.

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FREE PRODUCT

Everyone can direct projects

AI-agent-powered project management lets every teammate coordinate agents to deliver complex work.

  • ✓Agents understand intent, break down steps, plan work, and run workflows without hand-by-hand assignment
  • ✓No more chasing progress or delivery — agents keep every execution step moving
  • ✓Sign up and start with your existing workflow; no rip-and-replace migration required
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Everyone can direct projects — agents execute project tasks autonomously
MORE THAN A TOOL

Your agent is a project partner

Agents do more than execute commands. They sense risk, remind you proactively, record decisions, and become trusted collaborators.

  • ✓Agents identify and flag delays and resource conflicts proactively
  • ✓The AuraBaba team uses it every day — we are our own first users
  • ✓Every version change and task owner is recorded for review and traceability
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Your agent is a project partner — collaboration dashboard and risk alerts
ENTERPRISE

Built for enterprise teams

From agent runtime to the management console, deploy everything in one place and start immediately.

OPERATIONS

Agent audit and health

Track every agent's execution history and runtime status in real time.

Agent operations · live monitoringOnlineHealth99.7%Active agents4824h runs / failures1,203 / 3Success rate trend (24h)[14:32:01] ✓ pipeline-deploy → complete 2.3s[14:28:44] ✓ data-sync-weekly → complete 8.1s[14:25:10] ! alert-threshold-hit → retrying
PROJECTS

Planning and risk control

See project schedules clearly, identify risks automatically, and keep delivery under control.

Project schedule · Q3 product iteration3 risksTasksJulAugHomepage refreshPaymentsMessagingUser systemAnalyticsDelayed2 resource conflicts1 serious delay
ADMIN

Team performance insights

Quantify output, find bottlenecks, and improve continuously with data.

Admin console · team performance overviewTeam output (this week)284tasksProductivity trend+18%vs last weekWeekly task completion trendMembersDoneAvg.Ming Zhang (FE)34Yue Li (BE)28Fang Wang (PM)22

The command line is the entry point

Connect to an agent workflow with one command, whether you work locally, on a server, or over SSH.

$ curl -fsSL https://aurababa.com/scripts/install.sh | bash $ aura setup # macOS / Linux; use it over SSH on servers and remote dev environments

Whether you are trying the free products or planning a tailored enterprise rollout

You can start here.

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FAQ

Frequently asked questions

Answers to the core questions about bringing agents into a team, private deployment, and pricing.

Q1

How is AuraBaba different from Feishu, DingTalk, or Jira?

Feishu and DingTalk are communication and collaboration tools, while Jira manages tasks. AuraBaba focuses on human-agent delivery: people make decisions while agents execute and track work. Traditional tools manage people's tasks; AuraBaba manages collaboration between people and agents.

Q2

What teams is AuraBaba for?

It is built for organizations bringing AI into their work, especially teams where AI capability is concentrated in a few people. Common cases include multi-agent software development, human-agent content operations, agent-assisted support, and any team turning AI from a personal tool into a shared capability.

Q3

Can a team without AI experience use AuraBaba?

Yes. No coding or prompt tuning is required. Create a project, add agents, and assign work after signing up. You can introduce agent collaboration gradually without rebuilding your existing workflow.

Q4

Does AuraBaba support private deployment?

Yes. Private deployments run on your own servers so data stays inside the company. Permissions can be scoped by project and member, and agent actions are fully auditable.

Q5

How does pricing work?

Core AuraBaba features are free, including multiple projects, multiple agents, and team collaboration. Documents consume credits. Contact us about private deployment.

Q6

How do agent tasks run?

You configure the runtime and connect a supported agent runtime. Agents are independent participants: after assignment they understand intent, break down steps, schedule work, execute, and record progress. They flag delays or conflicts and ask for human help when they cannot decide.

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