Runbear
FreemiumAI teammates for Slack that answer, act, and learn.
About Runbear
Runbear helps companies create and deploy custom AI agents, powered by LLMs like OpenAI Assistants and Anthropic Claude, directly within their communication and CRM platforms such as Slack, Microsoft Teams, HubSpot, Zendesk, and Discord. It enables users to build these AI agents without any coding or engineering assistance, typically in minutes, to automate repetitive tasks, enhance workflows, and improve team performance. These agents can learn from team chats, documents, and feedback, integrate with over 2,700 applications, and intelligently suggest and take over tasks.
How to Use
Users can build AI agents in minutes without coding or flowcharts. The process involves naming the agent, teaching it by connecting knowledge sources (like documents or chat history), and then letting it operate within existing communication platforms like Slack, Teams, or Discord. Agents learn from conversations, documents, and feedback, and can take action using various integrations.
Key Features
- No-code AI agent creation
- Seamless integration with Slack, Microsoft Teams, HubSpot, Discord
- Connects LLM apps like OpenAI Assistants and Anthropic Claude
- Learns from team chats, documents, and feedback
- Extensive integrations (2,700+ apps including Google Drive, Salesforce, Notion)
- Smart task delegation and automation
- Customizable AI user experiences
Use Cases
- Instantly query Excel reports in Slack
- Automate meeting preparation by pulling schedules and summaries
- Turn Slack conversations into organized Google Docs
- Build custom GPTs powered by HubSpot in Slack for CRM insights
- Enhance customer support with AI assistants in Slack/Teams/HubSpot
- Automate daily news summaries on selected topics
Key Features
Pros & Cons
- No-code setup in minutes, deploy in existing platforms
- Integrates with 2,000+ tools for context and actions
- Pre-emptive answers: reads tools before you open Slack
- Learns and adapts to team vocabulary and processes
- Per-user auth and SOC 2 compliance for security
- Flexible pricing per credit, no seat limits
- Auto-routes tasks to appropriate AI models
- Pricing based on credit system may be unpredictable for heavy usage
- Relies on external LLM providers; latency can vary
- Limited to text-based communication platforms (Slack, Teams, Discord) – no standalone interface
- Requires initial setup of agents and knowledge sources
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