Conversational agent builder
Describe an agent in natural language, refine its rules in conversation, preview the result, and publish it with one click. Templates cover more than 50 industry and role starting points.
ZooWork
ZooWork is an AI agent platform for businesses to build and run agents using company knowledge, tools, and workflows to plan tasks and deliver work.
AI agents for business workflows
ZooWork is an AI agent platform for building, deploying, and running agents that carry out business workflows. Users can package role knowledge, company data, policies, SOPs, standards, and tool permissions into an agent rather than starting from a blank prompt.
Agents can plan multi-step work, use connected systems, ask for approval before selected changes, and return operational deliverables such as reports, drafts, decks, orders, and system updates. The platform supports workspace-based use, workplace messaging, embedded experiences, and product integrations through API-oriented options.
Core capabilities
Managed execution with approvals
The runtime plans complex work, breaks it into steps, executes tool calls, records progress, and pauses for human approval before selected actions that can change data or move money.
Business knowledge and structured data
Agents can be grounded in company knowledge, industry context, policies, working SOPs, delivery standards, and role-specific skills. ZooData can turn URLs into structured, agent-ready JSON and is presented for sources including e-commerce, finance, food delivery, and social platforms.
Multi-model access and routing
ZooWork provides access to multiple model families, including OpenAI, Claude, Gemini, DeepSeek, Kimi, GLM, and Seedance, while its enterprise model gateway describes routing and BYOK support.
Deployment and system connections
Agents can run in the ZooWork app, supported workplace messaging channels, embedded business systems, or through API and SDK patterns shown on the site. Named connections include Google Workspace, Microsoft 365, Slack, Lark, Jira, and GitHub, with MCP compatibility for internal tools.
Runtime controls and governance
The platform supports triggers and scheduled tasks, isolated Python, Shell, and Browser sandboxes, cloud autoscaling, and observability for agent runs. Enterprise materials also describe role permissions, policy checks, encryption, tenant isolation, and audit trails.
Practical use cases
Retail inventory and replenishment
A store operations agent can read inventory and sell-through data, forecast near-term demand, identify stores at risk of stockouts, prepare replenishment actions, request approval, and re-check results on a schedule.
Sales pipeline review
Sales and CRM teams can use an agent to fetch open opportunities, cross-reference CRM records, and produce a pipeline view showing stages, amounts, close dates, probabilities, and owners.
Marketing and proposal production
Marketing teams and agencies can turn briefs into proposal drafts, coordinate campaign work, and repurpose source content into posts and emails while keeping the message consistent.
Investment and competitive research
Research teams can organize market signals, company information, and evidence into recurring preparation work, helping analysts spend more time evaluating findings than gathering them.
Manufacturing exception management
Manufacturing operations teams can bring production alerts and material needs together, diagnose exceptions, and prepare reports or next-shift actions for review.
Pros and Cons
Pros
- Build agents conversationally or start from more than 50 industry and role templates.
- Supports planning, tool use, scheduled follow-ups, human approval gates, and deliverables beyond conversational answers.
- Connects agent work to business knowledge and named workplace, productivity, development, and enterprise systems.
- Offers multiple model families, structured web data collection through ZooData, and deployment options spanning workspace, messaging, embedded use, and API paths.
Cons
- The site does not provide a complete public list of supported connectors, API specifications, or detailed limitations for every workflow.
- Advanced deployment and enterprise capabilities may require separate qualification or a sales process.
- Agents that act on live business systems require configuration of permissions, tools, and approval rules before they can perform consequential work.
FAQ
How do you build an agent in ZooWork?
Yes. ZooWork's Agent Builder lets users describe an agent in conversation, add rules, preview it, and publish it. The site also lists more than 50 industry agent templates as starting points.
What can ZooWork agents produce?
Agents can work with business knowledge, company data, SOPs, delivery standards, and permitted tools. The platform describes outputs including first drafts, decks, documents, orders, reports, and ERP updates, with approval required for selected actions.
What systems and channels can ZooWork connect to?
The site names Google Workspace, Microsoft 365, Slack, Lark, Jira, and GitHub, and says the platform is MCP-compatible for internal tools or data sources. IM channels listed on the site include ZooWork, Slack, Microsoft Teams, and WhatsApp.
How is ZooWork offered and priced?
The Pro Agent Builder plan is listed at $30 per month and includes 6,000 monthly credits plus a limited-time 14,000-credit bonus, along with specified compute and storage. ZooWork also offers a Managed Agent API and an Enterprise path, with details handled separately.
Quick Facts
- Category
- AI agent platform and business automation
- Primary users
- Domain experts, forward-deployed engineers, business teams, and enterprise organizations
- Build options
- ZooWork Agent Builder, Managed Agent API, and Enterprise
- Template library
- 50+ industry and role agent templates
- Listed Pro price
- $30/month, with 6,000 monthly credits and a limited-time 14,000-credit bonus
- Source domain
- zoowork.ai
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