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Automate wit.ai workflows with AI Agents

Enable your team to trigger AI agent FAQ responses in Slack using wit.ai-powered voice or text, saving time and boosting consistency. Enhance your wit.ai workflows with AI-powered automation in Slack, Teams, and Discord.

Automate FAQs with Voice Commands
Enable your team to trigger AI agent FAQ responses in Slack using wit.ai-powered voice or text, saving time and boosting consistency.
Daily Briefings from Team Conversations
The AI agent uses wit.ai understanding to analyze Slack discussions and deliver scheduled briefings in natural language summaries.
Turn Spoken Ideas into Action Items
Team members speak tasks in chat; the wit.ai-trained agent extracts and assigns them directly into team project boards.
Voice-Driven Knowledge Search
Ask your AI agent questions using natural voice/text, retrieving answers from synced docs for seamless team information flow.
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In today’s fast-paced workplaces, teams crave smarter ways to collaborate, retrieve information, and automate daily workflows. wit.ai is a leader in natural language processing, making it easier to build voice- and text-driven applications. But what happens when you combine wit.ai’s intelligent language understanding with Runbear’s AI agent platform inside tools like Slack and Teams? The result: a seamless transformation of your team’s communication channels into action-oriented, knowledge-rich hubs powered by conversational AI.

About wit.ai

wit.ai is an open-source natural language processing platform owned by Facebook (Meta) that allows teams and developers to build flexible voice and text interfaces for their apps and devices. It translates human language—either spoken or typed—into structured data (intents and entities) that apps can use to take action. wit.ai is popular among developers building chatbots, voice assistants, smart home controllers, and any app needing robust language understanding. Its open, API-driven approach makes it suitable for organizations wanting conversational UX without building an NLP stack from scratch. Teams typically use wit.ai to power user interactions in messaging, customer support, or automation applications, but those features previously lived outside of default team workflows like Slack or Teams—limiting real-time collaboration and action.

Use Cases in Practice

Let’s dig deeper into how teams are amplifying their productivity and collaboration by uniting wit.ai with Runbear’s AI agents. Instead of just parsing messages, AI agents can listen for team questions or spoken commands inside Slack, instantly respond with answers sourced from your documentation, or automate daily routines. For example, when a manager voices, 'Summarize today’s support tickets,' the AI agent leverages wit.ai’s language model to recognize the request and fetches insights directly from synced data, eliminating time-consuming manual checks. Similarly, spoken tasks like 'Add budget review to our action items' can be captured, structured, and assigned—without ever leaving your chat. Weekly briefings, real-time FAQ assistance, and even in-depth data analysis all become accessible at the speed of conversation. For teams intrigued by natural language analytics, see also how we instantly query Excel reports in Slack and simplify business analytics with AI, both of which become even more powerful with voice-driven triggers from wit.ai.

wit.ai vs wit.ai + AI Agent: Key Differences

wit.ai Comparison Table

wit.ai alone lets teams build natural language interfaces, but keeping conversations, knowledge, and automation siloed. Integrating with Runbear supercharges wit.ai by connecting NLP to your team's chat, unlocking knowledge retrieval, instant action, and teamwork. With Runbear, AI agents don’t just understand — they act, analyze, and automate in the channels your team lives in.

Implementation Considerations

Teams looking to leverage wit.ai alone face key challenges: initial setup requires technical expertise, connecting language understanding to business workflow demands custom coding, and knowledge management remains isolated. Seamless team adoption isn’t automatic—employees must switch apps, and data privacy is often a concern. When layering Runbear’s AI agent, teams should prepare by aligning team chat adoption, ensuring internal documentation (e.g., Notion or Drive) is accessible for syncing, and defining core workflows. Change management will include lightweight training on using voice/text commands in chat. Assess team readiness, permissions needed for data sync, and the ROI versus ongoing maintenance of classic NLP projects. Most crucially, shift the team mindset: actionable AI doesn’t just answer questions, it can drive task execution and team performance—when integrated thoughtfully.

Get Started Today

Bringing wit.ai into the Runbear ecosystem turns passive language understanding into hands-on team impact. Why settle for isolated chatbots or siloed voice features when you can launch an AI agent that’s conversational, proactive, and tightly woven into your team’s workflows? Take the leap: let your team experience AI agents that hear, act, and empower real collaboration—starting right inside your daily chat. Get started with Runbear and wit.ai today to unlock new levels of team productivity and seamless automation.